Simulace.info - User contributions [en]

WS 2017/2018

2018-01-24T20:10:13Z

Xbilr00:

Semestral papers from winter term 2017/2018. Please, put here links to the pages with your paper. First you need to have your [[Assignments WS 2017/2018|assignment approved]]

==Simulations==

--[[User:feld00|feld00]] ([[User feld00|talk]]) 18:39, 15 January 2018 (CET) [[Evacuation from a custom building]]

--[[User:A_V|Aslanova_V]] ([[User A_V|talk]]) 20:00, 15 January 2018 (CET) [[Hamsters Spawning]]

--[[User:Amelievh|Amelievh]] ([[User talk:Amelievh|talk]]) 00:12, 16 January 2018 (CET) [[Gender Pay Gap]]

--[[User:Mamo00|Mamo00]] ([[User Mamo00|talk]]) 00:23, 16 January 2018 (CET) [[Australian Shepherd]]

--[[User:Alrw00|Alrw00]] ([[User Alrw00|talk]]) 19:23, 16 January 2018 (CET) [[H1N1]]

--[[User:Yaua00|Yaua00]] ([[User talk:Yaua00|talk]]) 21:32, 16 January 2018 (CET) [[Chickenpox]]

--[[User:xbilr00|xbilr00]] ([[User talk:xbilr00|talk]]) 0:10, 17 January 2018 (CET) [[Government Policies Impact]]

--[[User:Hram00|Hram00]] ([[User talk:Hram00|talk]]) 09:04, 17 January 2018 (CET) [[Jellyfish problem]]

--[[User:Zotv01|Zotv01]] ([[User talk:Zotv01|talk]]) 12:54, 17 January 2018 (CET) [[Ophthalmology Department]]

--[[User:Ewoud Stroom|Ewoud Stroom]] ([[User talk:Ewoud Stroom|talk]]) 12:35, 23 January 2018 (CET) [[Overfishing problem]]

==Papers==
--[[User:feld00|feld00]] ([[User feld00|talk]]) 15:47, 22 January 2018 (CET) [[Agent Environments]]

--[[User:Yaua00|Yaua00]] ([[User talk:Yaua00|talk]]) 17:06, 23 January 2018 (CET) [[MonteCarloMethod]]

--[[User:A_V|Aslanova_V]] ([[User talk:A V|talk]]) 10:42, 24 January 2018 (CET) [[Conceptual Graphs (WS 2017 /2018)]]

--[[User:Alrw00|Alrw00]] ([[User talk:A V|talk]]) 14:48, 24 January 2018 (CET) [[Vickrey Auction (WS 2017 /2018)]]

--[[User:Mamo00|Mamo00]] ([[User talk:Mamo00|talk]]) 19:04, 24 January 2018 (CET) [[Interpretation of MC simulation results (Stochastic methods)]]

--[[User:xbilr00|xbilr00]] ([[User talk:xbilr00|talk]]) 21:10, 24 January 2018 (CET) [[Agents Reasoning]]

Agents Reasoning

2018-01-24T20:08:55Z

Xbilr00:

== Introduction ==

In order the agents can make the decisions, they have to be able to evaluate the external environment. But when we talk about the computer agents, they are nothings else than bunch of 0 and 1. So as the basic step we have to set the rules for evaluating the external reality.
For describing these rules, there are many complex models of agents reasoning. They describe the way how an agent understands its external environment and what are its reactions for the accepted inputs. The goal of this article is describing the most common ones and explaining their optimal using.

Before I start with the description, it is good to realize that some models can be used only for single-agent systems, some for multi-agent systems and some for both. In most of cases the description of selected model’s principles shows for which kind of systems the model can be used.

== Case-Based Reasoning ==

Case-Based Reasoning is that type of reasoning that most of the people probably imagine at first. Generally we can say it is based on very simple if-then principle.<ref>AHA, David W., Leonard A. BRESLOW a Héctor MUÑOZ-AVILA. Conversational Case-Based Reasoning. Applied Intelligence [online]. 2001, vol. 14, no. 1, s. 9-32. ISSN 0924669X.</ref> Although it can sounds quite primitive, in many occasion it can still be the best choice.

== CARDS ==

CARDS is a model of case-based reasoning used for multiagent systems. The acronym means case-based reasoning decision support. It sets the principles of negotiating where more agents are present. <ref>LI, Jing a Zhaohan SHENG. A multi-agent model for the reasoning of uncertainty information in supply chains. International Journal of Production Research [online]. 2011, 49(19), 5737-5753 [cit. 2018-01-24]. DOI: 10.1080/00207543.2010.524257. ISSN 0020-7543. Available from: http://www.tandfonline.com/doi/abs/10.1080/00207543.2010.524257</ref>

== BDI Model ==

The BDI acronym means Belief-Desire-Intention. The Beliefs are the representatives of information an agent has received about itself or about its environment (for example a robot at Mars knows the external temperature, the terrain etc.). The Desires represent the activity done by an agent (it wants to collect a stone). The intentions are the goals of an agency while doing the desires (it has to collect at least 5 various kind of stones at Mars). <ref>DUFF, Simon. Maintenance Goals in Intelligent Systems. Computational intelligence [online]. [cit. 2018-01-24]. ISSN 0824-7935.</ref>

== Biased Reasoning ==

The biased reasoning is more similar to the human mind than the previously mentioned ones. It is able to put ahead agent’s experience over strictly rational reasoning. <ref>HEUVELINK, Annerieke, Michel C.A. KLEIN a Jan TREUR. An Agent Memory Model Enabling Rational and Biased Reasoning. 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology [online]. IEEE, 2008, 2008, , 193-199 [cit. 2018-01-24]. DOI: 10.1109/WIIAT.2008.274. ISBN 978-0-7695-3496-1. Available from: http://ieeexplore.ieee.org/document/4740621/</ref>

Agents Reasoning

2018-01-24T20:08:31Z

Xbilr00: Created page with " == Introduction == In order the agents can make the decisions, they have to be able to evaluate the external environment. But when we talk about the computer agents, they ar..."

== Introduction ==

In order the agents can make the decisions, they have to be able to evaluate the external environment. But when we talk about the computer agents, they are nothings else than bunch of 0 and 1. So as the basic step we have to set the rules for evaluating the external reality.
For describing these rules, there are many complex models of agents reasoning. They describe the way how an agent understands its external environment and what are its reactions for the accepted inputs. The goal of this article is describing the most common ones and explaining their optimal using.
Before I start with the description, it is good to realize that some models can be used only for single-agent systems, some for multi-agent systems and some for both. In most of cases the description of selected model’s principles shows for which kind of systems the model can be used.

== Case-Based Reasoning ==

Case-Based Reasoning is that type of reasoning that most of the people probably imagine at first. Generally we can say it is based on very simple if-then principle.<ref>AHA, David W., Leonard A. BRESLOW a Héctor MUÑOZ-AVILA. Conversational Case-Based Reasoning. Applied Intelligence [online]. 2001, vol. 14, no. 1, s. 9-32. ISSN 0924669X.</ref> Although it can sounds quite primitive, in many occasion it can still be the best choice.

== CARDS ==

CARDS is a model of case-based reasoning used for multiagent systems. The acronym means case-based reasoning decision support. It sets the principles of negotiating where more agents are present. <ref>LI, Jing a Zhaohan SHENG. A multi-agent model for the reasoning of uncertainty information in supply chains. International Journal of Production Research [online]. 2011, 49(19), 5737-5753 [cit. 2018-01-24]. DOI: 10.1080/00207543.2010.524257. ISSN 0020-7543. Available from: http://www.tandfonline.com/doi/abs/10.1080/00207543.2010.524257</ref>

== BDI Model ==

The BDI acronym means Belief-Desire-Intention. The Beliefs are the representatives of information an agent has received about itself or about its environment (for example a robot at Mars knows the external temperature, the terrain etc.). The Desires represent the activity done by an agent (it wants to collect a stone). The intentions are the goals of an agency while doing the desires (it has to collect at least 5 various kind of stones at Mars). <ref>DUFF, Simon. Maintenance Goals in Intelligent Systems. Computational intelligence [online]. [cit. 2018-01-24]. ISSN 0824-7935.</ref>

== Biased Reasoning ==

The biased reasoning is more similar to the human mind than the previously mentioned ones. It is able to put ahead agent’s experience over strictly rational reasoning. <ref>HEUVELINK, Annerieke, Michel C.A. KLEIN a Jan TREUR. An Agent Memory Model Enabling Rational and Biased Reasoning. 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology [online]. IEEE, 2008, 2008, , 193-199 [cit. 2018-01-24]. DOI: 10.1109/WIIAT.2008.274. ISBN 978-0-7695-3496-1. Available from: http://ieeexplore.ieee.org/document/4740621/</ref>

Government Policies Impact

2018-01-16T23:15:48Z

Xbilr00:

== Introduction ==

As my semester project I decided to examine possible government’s impact on the economic performance of a country. It means whether a government is able to influence the economic performance by its policies.

I also wanted to prove the neoclassic economic theory saying that decreasing taxes is beneficial to the economic growth.

The project’s goal is simulating a simple environment which can be helpful for setting suitable government policies.

== Methods Used ==

For my project I used the simulation method '''Monte Carlo'''. I combined this method with '''regressive analysis''' proving that the data selected by me are suitable for my experiment.

== Data ==

I decided to examine my theories on data from the Czech economy from 2008 to 2016 (data from 2017 are still not completely published). These data were released by Czech Statistical Office and Ministry of Finance of the Czech Republic.

As the indicator of economic performance I decided to use gross domestic product (GDP). Despite all criticism, I still recognize it as the most relevant economic state indicator of a selected economy. The commonly recognized theories are saying the GDP is created by consumption, investments, government spending and export. This should be reflected in possible government tools.
As the government tools I decided to select those 4:

1. '''Individual Income Tax Rate.''' I believe this tax is important because in the Czech economics it taxes all wages of employees and self-employers. The tax rate can have influence on civil consumption and investments.

2. '''Corporate Income Tax Rate.''' I believe this tax is important because it taxes the profits of corporations in the Czech economy. The tax rate can have influence on civil consumption and investments.

3. '''Government Spending.''' By the most of mainstream economics theories a government can affects economy by government spending at least in short-run, so I decided to use it in my simulation.

4. '''Net Export.''' This factor is the most controversial and I considered really long time if should I use it in my model. Although a government cannot directly affect the net export (foreign trade is done by businesses, not government), it is commonly recognized a government can affect it indirectly by its pro-export or protectionists policies. This is a reason why I decided to use it in my model after proper consideration.

For my model I did a large simplification of reality. For example I did not used in my model value added tax (VAT) despite the fact is affects a consumption. The problem is VAT has 2 levels and some items are even not taxed by VAT, so reflecting this tax in my model would be extremely complicated. In reality a government uses more tools for reaching its economics goals.

I also realize a term from 2008 to 2016 can be too short in some cases. But I decided for this term based on fact in 2008 a lot of important tax changes came in legal power (for example flat individual income tax). By involving data from the previous years to my model, this can bring certain complication for result’s interpretation.

Even with these simplifications my model is not loosing its relevance. My goals were not involving all the government tools to my model but defining clear rules for setting the government policies.

== Simulation and Modelling ==

For proving the relevance of selected economic tools I used '''regressive analysis'''. Then I did '''Monte Carlo Simulation'''.

== Regressive Analysis ==

Before using Monte Carlo I had to prove the influence of selected tools to the economic performance (GDP). For this purpose I used regressive analysis. The '''R rate was 0,877068461027525'''. This proves the tools selected by me have certain impact on the output (not the full one as I will explain later).

I also got coefficients for selected tools representing their contribution to the output. Since the individual income tax rate is still the same since 2008, its coefficient was 0 (based on this tool is not relevant for my future steps). For the other tools I got following coefficients:
Corporate Income Tax Rate = 12994,6878898414
Government Spending = 2,95223111181548
Net Export = 2,79310070627737

== Monte Carlo Simulation ==

When I had this done, I did Monte Carlo Simulation. With random numbers generator I generated random possible GDP values. Then I divided these values by the coefficients I got from regressive analysis. Based on this I set the values of all government tools necessary for reaching the selected GDP value.
== Conclusion ==
The Monte Carlo simulation '''helped me to set the ideal values of the government tools for reaching certain level of GDP'''. This can be used for proposing the government policies enhancing an economic growth.

My simulation also '''did not prove the principles of neoclassic economics'''. The situations with the highest GDP were also situations with the highest income tax rates which is a right opposite of the neoclassic economic theory. In these situations the government spending was also the highest, so we can even say my simulation '''proves more the principles of Keynesian economics'''.

But this does not mean my simulation totally rejected the neoclassic economics theories. There are just more important factors directly influencing GDP than tax rates. Even the simulation is favouring the high taxes, we can still expect lowering the taxes have positive indirect impact on factors like consumption and investments which have direct impact on GDP but they are not under full control of a government, so they were not included in my simulation. This is also proved by a fact the fact R rate was only 0,877068461027525 (it means there are more factors having impact on GDP growth).

It is also good to realize the sources are not unlimited. With ignoring the other economic facts, my model can lead to an idea that for ensuring GDP growth, you just need to tax people more and spend more money. But the reality is much more difficult. Every government is supposed to behave fiscally responsible, so it has to keep the deficit and public debt under control. The Laffer Curve also proves you cannot raise the tax rate above certain level.

== Source File ==
[http://www.simulace.info/index.php/File:Monte_Carlo-Government_Policies.xlsx Monte Carlo-Government Policies.xlsx]

Government Policies Impact

2018-01-16T23:15:33Z

Xbilr00:

== Introduction ==

As my semester project I decided to examine possible government’s impact on the economic performance of a country. It means whether a government is able to influence the economic performance by its policies.

I also wanted to prove the neoclassic economic theory saying that decreasing taxes is beneficial to the economic growth.

The project’s goal is simulating a simple environment which can be helpful for setting suitable government policies.

== Methods Used ==

For my project I used the simulation method '''Monte Carlo'''. I combined this method with '''regressive analysis''' proving that the data selected by me are suitable for my experiment.

== Data ==

I decided to examine my theories on data from the Czech economy from 2008 to 2016 (data from 2017 are still not completely published). These data were released by Czech Statistical Office and Ministry of Finance of the Czech Republic.

As the indicator of economic performance I decided to use gross domestic product (GDP). Despite all criticism, I still recognize it as the most relevant economic state indicator of a selected economy. The commonly recognized theories are saying the GDP is created by consumption, investments, government spending and export. This should be reflected in possible government tools.
As the government tools I decided to select those 4:
1. '''Individual Income Tax Rate.''' I believe this tax is important because in the Czech economics it taxes all wages of employees and self-employers. The tax rate can have influence on civil consumption and investments.

2. '''Corporate Income Tax Rate.''' I believe this tax is important because it taxes the profits of corporations in the Czech economy. The tax rate can have influence on civil consumption and investments.

3. '''Government Spending.''' By the most of mainstream economics theories a government can affects economy by government spending at least in short-run, so I decided to use it in my simulation.

4. '''Net Export.''' This factor is the most controversial and I considered really long time if should I use it in my model. Although a government cannot directly affect the net export (foreign trade is done by businesses, not government), it is commonly recognized a government can affect it indirectly by its pro-export or protectionists policies. This is a reason why I decided to use it in my model after proper consideration.

For my model I did a large simplification of reality. For example I did not used in my model value added tax (VAT) despite the fact is affects a consumption. The problem is VAT has 2 levels and some items are even not taxed by VAT, so reflecting this tax in my model would be extremely complicated. In reality a government uses more tools for reaching its economics goals.

I also realize a term from 2008 to 2016 can be too short in some cases. But I decided for this term based on fact in 2008 a lot of important tax changes came in legal power (for example flat individual income tax). By involving data from the previous years to my model, this can bring certain complication for result’s interpretation.

Even with these simplifications my model is not loosing its relevance. My goals were not involving all the government tools to my model but defining clear rules for setting the government policies.

== Simulation and Modelling ==

For proving the relevance of selected economic tools I used '''regressive analysis'''. Then I did '''Monte Carlo Simulation'''.

== Regressive Analysis ==

Before using Monte Carlo I had to prove the influence of selected tools to the economic performance (GDP). For this purpose I used regressive analysis. The '''R rate was 0,877068461027525'''. This proves the tools selected by me have certain impact on the output (not the full one as I will explain later).

I also got coefficients for selected tools representing their contribution to the output. Since the individual income tax rate is still the same since 2008, its coefficient was 0 (based on this tool is not relevant for my future steps). For the other tools I got following coefficients:
Corporate Income Tax Rate = 12994,6878898414
Government Spending = 2,95223111181548
Net Export = 2,79310070627737

== Monte Carlo Simulation ==

When I had this done, I did Monte Carlo Simulation. With random numbers generator I generated random possible GDP values. Then I divided these values by the coefficients I got from regressive analysis. Based on this I set the values of all government tools necessary for reaching the selected GDP value.
== Conclusion ==
The Monte Carlo simulation '''helped me to set the ideal values of the government tools for reaching certain level of GDP'''. This can be used for proposing the government policies enhancing an economic growth.

My simulation also '''did not prove the principles of neoclassic economics'''. The situations with the highest GDP were also situations with the highest income tax rates which is a right opposite of the neoclassic economic theory. In these situations the government spending was also the highest, so we can even say my simulation '''proves more the principles of Keynesian economics'''.

But this does not mean my simulation totally rejected the neoclassic economics theories. There are just more important factors directly influencing GDP than tax rates. Even the simulation is favouring the high taxes, we can still expect lowering the taxes have positive indirect impact on factors like consumption and investments which have direct impact on GDP but they are not under full control of a government, so they were not included in my simulation. This is also proved by a fact the fact R rate was only 0,877068461027525 (it means there are more factors having impact on GDP growth).

It is also good to realize the sources are not unlimited. With ignoring the other economic facts, my model can lead to an idea that for ensuring GDP growth, you just need to tax people more and spend more money. But the reality is much more difficult. Every government is supposed to behave fiscally responsible, so it has to keep the deficit and public debt under control. The Laffer Curve also proves you cannot raise the tax rate above certain level.

== Source File ==
[http://www.simulace.info/index.php/File:Monte_Carlo-Government_Policies.xlsx Monte Carlo-Government Policies.xlsx]

WS 2017/2018

2018-01-16T23:13:46Z

Xbilr00: /* Simulations */

WS 2017/2018

2018-01-16T23:12:38Z

Xbilr00: /* Simulations */

Government Policies Impact

2018-01-16T23:10:49Z

Xbilr00:

== Introduction ==

As my semester project I decided to examine possible government’s impact on the economic performance of a country. It means whether a government is able to influence the economic performance by its policies.

I also wanted to prove the neoclassic economic theory saying that decreasing taxes is beneficial to the economic growth.

The project’s goal is simulating a simple environment which can be helpful for setting suitable government policies.

== Methods Used ==

For my project I used the simulation method '''Monte Carlo'''. I combined this method with '''regressive analysis''' proving that the data selected by me are suitable for my experiment.

== Data ==

I decided to examine my theories on data from the Czech economy from 2008 to 2016 (data from 2017 are still not completely published). These data were released by Czech Statistical Office and Ministry of Finance of the Czech Republic.

As the indicator of economic performance I decided to use gross domestic product (GDP). Despite all criticism, I still recognize it as the most relevant economic state indicator of a selected economy. The commonly recognized theories are saying the GDP is created by consumption, investments, government spending and export. This should be reflected in possible government tools.
As the government tools I decided to select those 4:
1. '''Individual Income Tax Rate.''' I believe this tax is important because in the Czech economics it taxes all wages of employees and self-employers. The tax rate can have influence on civil consumption and investments.
2. '''Corporate Income Tax Rate.''' I believe this tax is important because it taxes the profits of corporations in the Czech economy. The tax rate can have influence on civil consumption and investments.
3. '''Government Spending.''' By the most of mainstream economics theories a government can affects economy by government spending at least in short-run, so I decided to use it in my simulation.
4. '''Net Export.''' This factor is the most controversial and I considered really long time if should I use it in my model. Although a government cannot directly affect the net export (foreign trade is done by businesses, not government), it is commonly recognized a government can affect it indirectly by its pro-export or protectionists policies. This is a reason why I decided to use it in my model after proper consideration.

For my model I did a large simplification of reality. For example I did not used in my model value added tax (VAT) despite the fact is affects a consumption. The problem is VAT has 2 levels and some items are even not taxed by VAT, so reflecting this tax in my model would be extremely complicated. In reality a government uses more tools for reaching its economics goals.

I also realize a term from 2008 to 2016 can be too short in some cases. But I decided for this term based on fact in 2008 a lot of important tax changes came in legal power (for example flat individual income tax). By involving data from the previous years to my model, this can bring certain complication for result’s interpretation.

Even with these simplifications my model is not loosing its relevance. My goals were not involving all the government tools to my model but defining clear rules for setting the government policies.

== Simulation and Modelling ==

For proving the relevance of selected economic tools I used '''regressive analysis'''. Then I did '''Monte Carlo Simulation'''.

== Regressive Analysis ==

Before using Monte Carlo I had to prove the influence of selected tools to the economic performance (GDP). For this purpose I used regressive analysis. The '''R rate was 0,877068461027525'''. This proves the tools selected by me have certain impact on the output (not the full one as I will explain later).

I also got coefficients for selected tools representing their contribution to the output. Since the individual income tax rate is still the same since 2008, its coefficient was 0 (based on this tool is not relevant for my future steps). For the other tools I got following coefficients:
Corporate Income Tax Rate = 12994,6878898414
Government Spending = 2,95223111181548
Net Export = 2,79310070627737

== Monte Carlo Simulation ==

When I had this done, I did Monte Carlo Simulation. With random numbers generator I generated random possible GDP values. Then I divided these values by the coefficients I got from regressive analysis. Based on this I set the values of all government tools necessary for reaching the selected GDP value.
== Conclusion ==
The Monte Carlo simulation '''helped me to set the ideal values of the government tools for reaching certain level of GDP'''. This can be used for proposing the government policies enhancing an economic growth.

My simulation also '''did not prove the principles of neoclassic economics'''. The situations with the highest GDP were also situations with the highest income tax rates which is a right opposite of the neoclassic economic theory. In these situations the government spending was also the highest, so we can even say my simulation '''proves more the principles of Keynesian economics'''.

But this does not mean my simulation totally rejected the neoclassic economics theories. There are just more important factors directly influencing GDP than tax rates. Even the simulation is favouring the high taxes, we can still expect lowering the taxes have positive indirect impact on factors like consumption and investments which have direct impact on GDP but they are not under full control of a government, so they were not included in my simulation. This is also proved by a fact the fact R rate was only 0,877068461027525 (it means there are more factors having impact on GDP growth).

It is also good to realize the sources are not unlimited. With ignoring the other economic facts, my model can lead to an idea that for ensuring GDP growth, you just need to tax people more and spend more money. But the reality is much more difficult. Every government is supposed to behave fiscally responsible, so it has to keep the deficit and public debt under control. The Laffer Curve also proves you cannot raise the tax rate above certain level.

== Source File ==
[http://www.simulace.info/index.php/File:Monte_Carlo-Government_Policies.xlsx Monte Carlo-Government Policies.xlsx]

Government Policies Impact

2018-01-16T23:06:17Z

Xbilr00: /* == Conclusion == */

== Introduction ==

As my semester project I decided to examine possible government’s impact on the economic performance of a country. It means whether a government is able to influence the economic performance by its policies.
I also wanted to prove the neoclassic economic theory saying that decreasing taxes is beneficial to the economic growth.
The project’s goal is simulating a simple environment which can be helpful for setting suitable government policies.

== Methods Used ==

For my project I used the simulation method Monte Carlo. I combined this method with regressive analysis proving that the data selected by me are suitable for my experiment.
Data
I decided to examine my theories on data from the Czech economy from 2008 to 2016 (data from 2017 are still not completely published). These data were released by Czech Statistical Office and Ministry of Finance of the Czech Republic.
As the indicator of economic performance I decided to use gross domestic product (GDP). Despite all criticism, I still recognize it as the most relevant economic state indicator of a selected economy. The commonly recognized theories are saying the GDP is created by consumption, investments, government spending and export. This should be reflected in possible government tools.
As the government tools I decided to select those 4:
1. Individual Income Tax Rate. I believe this tax is important because in the Czech economics it taxes all wages of employees and self-employers. The tax rate can have influence on civil consumption and investments.
2. Corporate Income Tax Rate. I believe this tax is important because it taxes the profits of corporations in the Czech economy. The tax rate can have influence on civil consumption and investments.
3. Government Spending. By the most of mainstream economics theories a government can affects economy by government spending at least in short-run, so I decided to use it in my simulation.
4. Net Export. This factor is the most controversial and I considered really long time if should I use it in my model. Although a government cannot directly affect the net export (foreign trade is done by businesses, not government), it is commonly recognized a government can affect it indirectly by its pro-export or protectionists policies. This is a reason why I decided to use it in my model after proper consideration.
For my model I did a large simplification of reality. For example I did not used in my model value added tax (VAT) despite the fact is affects a consumption. The problem is VAT has 2 levels and some items are even not taxed by VAT, so reflecting this tax in my model would be extremely complicated. In reality a government uses more tools for reaching its economics goals.
I also realize a term from 2008 to 2016 can be too short in some cases. But I decided for this term based on fact in 2008 a lot of important tax changes came in legal power (for example flat individual income tax). By involving data from the previous years to my model, this can bring certain complication for result’s interpretation.
Even with these simplifications my model is not loosing its relevance. My goals were not involving all the government tools to my model but defining clear rules for setting the government policies.

== Simulation and Modelling ==

For proving the relevance of selected economic tools I used regressive analysis. Then I did Monte Carlo Simulation.

== Regressive Analysis ==

Before using Monte Carlo I had to prove the influence of selected tools to the economic performance (GDP). For this purpose I used regressive analysis. The R rate was 0,877068461027525. This proves the tools selected by me have certain impact on the output (not the full one as I will explain later).
I also got coefficients for selected tools representing their contribution to the output. Since the individual income tax rate is still the same since 2008, its coefficient was 0 (based on this tool is not relevant for my future steps). For the other tools I got following coefficients:
Corporate Income Tax Rate = 12994,6878898414
Government Spending = 2,95223111181548
Net Export = 2,79310070627737

== Monte Carlo Simulation ==

When I had this done, I did Monte Carlo Simulation. With random numbers generator I generated random possible GDP values. Then I divided these values by the coefficients I got from regressive analysis. Based on this I set the values of all government tools necessary for reaching the selected GDP value.
== Conclusion ==
The Monte Carlo simulation helped me to set the ideal values of the government tools for reaching certain level of GDP. This can be used for proposing the government policies enhancing an economic growth.
My simulation also did not prove the principles of neoclassic economics. The situations with the highest GDP were also situations with the highest income tax rates which is a right opposite of the neoclassic economic theory. In these situations the government spending was also the highest, so we can even say my simulation proves more the principles of Keynesian economics.
But this does not mean my simulation totally rejected the neoclassic economics theories. There are just more important factors directly influencing GDP than tax rates. Even the simulation is favouring the high taxes, we can still expect lowering the taxes have positive indirect impact on factors like consumption and investments which have direct impact on GDP but they are not under full control of a government, so they were not included in my simulation. This is also proved by a fact the fact R rate was only 0,877068461027525 (it means there are more factors having impact on GDP growth).
It is also good to realize the sources are not unlimited. With ignoring the other economic facts, my model can lead to an idea that for ensuring GDP growth, you just need to tax people more and spend more money. But the reality is much more difficult. Every government is supposed to behave fiscally responsible, so it has to keep the deficit and public debt under control. The Laffer Curve also proves you cannot raise the tax rate above certain level.

== Source File ==
[http://www.simulace.info/index.php/File:Monte_Carlo-Government_Policies.xlsx Monte Carlo-Government Policies.xlsx]

Government Policies Impact

2018-01-16T23:05:59Z

Xbilr00:

== Introduction ==

As my semester project I decided to examine possible government’s impact on the economic performance of a country. It means whether a government is able to influence the economic performance by its policies.
I also wanted to prove the neoclassic economic theory saying that decreasing taxes is beneficial to the economic growth.
The project’s goal is simulating a simple environment which can be helpful for setting suitable government policies.

== Methods Used ==

For my project I used the simulation method Monte Carlo. I combined this method with regressive analysis proving that the data selected by me are suitable for my experiment.
Data
I decided to examine my theories on data from the Czech economy from 2008 to 2016 (data from 2017 are still not completely published). These data were released by Czech Statistical Office and Ministry of Finance of the Czech Republic.
As the indicator of economic performance I decided to use gross domestic product (GDP). Despite all criticism, I still recognize it as the most relevant economic state indicator of a selected economy. The commonly recognized theories are saying the GDP is created by consumption, investments, government spending and export. This should be reflected in possible government tools.
As the government tools I decided to select those 4:
1. Individual Income Tax Rate. I believe this tax is important because in the Czech economics it taxes all wages of employees and self-employers. The tax rate can have influence on civil consumption and investments.
2. Corporate Income Tax Rate. I believe this tax is important because it taxes the profits of corporations in the Czech economy. The tax rate can have influence on civil consumption and investments.
3. Government Spending. By the most of mainstream economics theories a government can affects economy by government spending at least in short-run, so I decided to use it in my simulation.
4. Net Export. This factor is the most controversial and I considered really long time if should I use it in my model. Although a government cannot directly affect the net export (foreign trade is done by businesses, not government), it is commonly recognized a government can affect it indirectly by its pro-export or protectionists policies. This is a reason why I decided to use it in my model after proper consideration.
For my model I did a large simplification of reality. For example I did not used in my model value added tax (VAT) despite the fact is affects a consumption. The problem is VAT has 2 levels and some items are even not taxed by VAT, so reflecting this tax in my model would be extremely complicated. In reality a government uses more tools for reaching its economics goals.
I also realize a term from 2008 to 2016 can be too short in some cases. But I decided for this term based on fact in 2008 a lot of important tax changes came in legal power (for example flat individual income tax). By involving data from the previous years to my model, this can bring certain complication for result’s interpretation.
Even with these simplifications my model is not loosing its relevance. My goals were not involving all the government tools to my model but defining clear rules for setting the government policies.

== Simulation and Modelling ==

For proving the relevance of selected economic tools I used regressive analysis. Then I did Monte Carlo Simulation.

== Regressive Analysis ==

Before using Monte Carlo I had to prove the influence of selected tools to the economic performance (GDP). For this purpose I used regressive analysis. The R rate was 0,877068461027525. This proves the tools selected by me have certain impact on the output (not the full one as I will explain later).
I also got coefficients for selected tools representing their contribution to the output. Since the individual income tax rate is still the same since 2008, its coefficient was 0 (based on this tool is not relevant for my future steps). For the other tools I got following coefficients:
Corporate Income Tax Rate = 12994,6878898414
Government Spending = 2,95223111181548
Net Export = 2,79310070627737

== Monte Carlo Simulation ==

When I had this done, I did Monte Carlo Simulation. With random numbers generator I generated random possible GDP values. Then I divided these values by the coefficients I got from regressive analysis. Based on this I set the values of all government tools necessary for reaching the selected GDP value.
== == Conclusion == ==
The Monte Carlo simulation helped me to set the ideal values of the government tools for reaching certain level of GDP. This can be used for proposing the government policies enhancing an economic growth.
My simulation also did not prove the principles of neoclassic economics. The situations with the highest GDP were also situations with the highest income tax rates which is a right opposite of the neoclassic economic theory. In these situations the government spending was also the highest, so we can even say my simulation proves more the principles of Keynesian economics.
But this does not mean my simulation totally rejected the neoclassic economics theories. There are just more important factors directly influencing GDP than tax rates. Even the simulation is favouring the high taxes, we can still expect lowering the taxes have positive indirect impact on factors like consumption and investments which have direct impact on GDP but they are not under full control of a government, so they were not included in my simulation. This is also proved by a fact the fact R rate was only 0,877068461027525 (it means there are more factors having impact on GDP growth).
It is also good to realize the sources are not unlimited. With ignoring the other economic facts, my model can lead to an idea that for ensuring GDP growth, you just need to tax people more and spend more money. But the reality is much more difficult. Every government is supposed to behave fiscally responsible, so it has to keep the deficit and public debt under control. The Laffer Curve also proves you cannot raise the tax rate above certain level.

== Source File ==
[http://www.simulace.info/index.php/File:Monte_Carlo-Government_Policies.xlsx Monte Carlo-Government Policies.xlsx]

Government Policies Impact

2018-01-16T23:05:24Z

Xbilr00:

== Introduction ==

As my semester project I decided to examine possible government’s impact on the economic performance of a country. It means whether a government is able to influence the economic performance by its policies.
I also wanted to prove the neoclassic economic theory saying that decreasing taxes is beneficial to the economic growth.
The project’s goal is simulating a simple environment which can be helpful for setting suitable government policies.

== Methods Used ==

For my project I used the simulation method Monte Carlo. I combined this method with regressive analysis proving that the data selected by me are suitable for my experiment.
Data
I decided to examine my theories on data from the Czech economy from 2008 to 2016 (data from 2017 are still not completely published). These data were released by Czech Statistical Office and Ministry of Finance of the Czech Republic.
As the indicator of economic performance I decided to use gross domestic product (GDP). Despite all criticism, I still recognize it as the most relevant economic state indicator of a selected economy. The commonly recognized theories are saying the GDP is created by consumption, investments, government spending and export. This should be reflected in possible government tools.
As the government tools I decided to select those 4:
1. Individual Income Tax Rate. I believe this tax is important because in the Czech economics it taxes all wages of employees and self-employers. The tax rate can have influence on civil consumption and investments.
2. Corporate Income Tax Rate. I believe this tax is important because it taxes the profits of corporations in the Czech economy. The tax rate can have influence on civil consumption and investments.
3. Government Spending. By the most of mainstream economics theories a government can affects economy by government spending at least in short-run, so I decided to use it in my simulation.
4. Net Export. This factor is the most controversial and I considered really long time if should I use it in my model. Although a government cannot directly affect the net export (foreign trade is done by businesses, not government), it is commonly recognized a government can affect it indirectly by its pro-export or protectionists policies. This is a reason why I decided to use it in my model after proper consideration.
For my model I did a large simplification of reality. For example I did not used in my model value added tax (VAT) despite the fact is affects a consumption. The problem is VAT has 2 levels and some items are even not taxed by VAT, so reflecting this tax in my model would be extremely complicated. In reality a government uses more tools for reaching its economics goals.
I also realize a term from 2008 to 2016 can be too short in some cases. But I decided for this term based on fact in 2008 a lot of important tax changes came in legal power (for example flat individual income tax). By involving data from the previous years to my model, this can bring certain complication for result’s interpretation.
Even with these simplifications my model is not loosing its relevance. My goals were not involving all the government tools to my model but defining clear rules for setting the government policies.

== Simulation and Modelling ==

For proving the relevance of selected economic tools I used regressive analysis. Then I did Monte Carlo Simulation.

== Regressive Analysis ==

Before using Monte Carlo I had to prove the influence of selected tools to the economic performance (GDP). For this purpose I used regressive analysis. The R rate was 0,877068461027525. This proves the tools selected by me have certain impact on the output (not the full one as I will explain later).
I also got coefficients for selected tools representing their contribution to the output. Since the individual income tax rate is still the same since 2008, its coefficient was 0 (based on this tool is not relevant for my future steps). For the other tools I got following coefficients:
Corporate Income Tax Rate = 12994,6878898414
Government Spending = 2,95223111181548
Net Export = 2,79310070627737

== Monte Carlo Simulation ==

When I had this done, I did Monte Carlo Simulation. With random numbers generator I generated random possible GDP values. Then I divided these values by the coefficients I got from regressive analysis. Based on this I set the values of all government tools necessary for reaching the selected GDP value.
== == Conclusion == ==
The Monte Carlo simulation helped me to set the ideal values of the government tools for reaching certain level of GDP. This can be used for proposing the government policies enhancing an economic growth.
My simulation also did not prove the principles of neoclassic economics. The situations with the highest GDP were also situations with the highest income tax rates which is a right opposite of the neoclassic economic theory. In these situations the government spending was also the highest, so we can even say my simulation proves more the principles of Keynesian economics.
But this does not mean my simulation totally rejected the neoclassic economics theories. There are just more important factors directly influencing GDP than tax rates. Even the simulation is favouring the high taxes, we can still expect lowering the taxes have positive indirect impact on factors like consumption and investments which have direct impact on GDP but they are not under full control of a government, so they were not included in my simulation. This is also proved by a fact the fact R rate was only 0,877068461027525 (it means there are more factors having impact on GDP growth).
It is also good to realize the sources are not unlimited. With ignoring the other economic facts, my model can lead to an idea that for ensuring GDP growth, you just need to tax people more and spend more money. But the reality is much more difficult. Every government is supposed to behave fiscally responsible, so it has to keep the deficit and public debt under control. The Laffer Curve also proves you cannot raise the tax rate above certain level.

== Source File ==
[http://www.simulace.info/index.php/File:Monte_Carlo-Government_Policies.xlsx Monte Carlo-Government Policies.xlsx]

Government Policies Impact

2018-01-16T23:04:33Z

Xbilr00: Created page with " == Introduction == As my semester project I decided to examine possible government’s impact on the economic performance of a country. It means whether a government is able..."

== Introduction ==

As my semester project I decided to examine possible government’s impact on the economic performance of a country. It means whether a government is able to influence the economic performance by its policies.
I also wanted to prove the neoclassic economic theory saying that decreasing taxes is beneficial to the economic growth.
The project’s goal is simulating a simple environment which can be helpful for setting suitable government policies.

== == Methods Used == ==

For my project I used the simulation method Monte Carlo. I combined this method with regressive analysis proving that the data selected by me are suitable for my experiment.
Data
I decided to examine my theories on data from the Czech economy from 2008 to 2016 (data from 2017 are still not completely published). These data were released by Czech Statistical Office and Ministry of Finance of the Czech Republic.
As the indicator of economic performance I decided to use gross domestic product (GDP). Despite all criticism, I still recognize it as the most relevant economic state indicator of a selected economy. The commonly recognized theories are saying the GDP is created by consumption, investments, government spending and export. This should be reflected in possible government tools.
As the government tools I decided to select those 4:
1. Individual Income Tax Rate. I believe this tax is important because in the Czech economics it taxes all wages of employees and self-employers. The tax rate can have influence on civil consumption and investments.
2. Corporate Income Tax Rate. I believe this tax is important because it taxes the profits of corporations in the Czech economy. The tax rate can have influence on civil consumption and investments.
3. Government Spending. By the most of mainstream economics theories a government can affects economy by government spending at least in short-run, so I decided to use it in my simulation.
4. Net Export. This factor is the most controversial and I considered really long time if should I use it in my model. Although a government cannot directly affect the net export (foreign trade is done by businesses, not government), it is commonly recognized a government can affect it indirectly by its pro-export or protectionists policies. This is a reason why I decided to use it in my model after proper consideration.
For my model I did a large simplification of reality. For example I did not used in my model value added tax (VAT) despite the fact is affects a consumption. The problem is VAT has 2 levels and some items are even not taxed by VAT, so reflecting this tax in my model would be extremely complicated. In reality a government uses more tools for reaching its economics goals.
I also realize a term from 2008 to 2016 can be too short in some cases. But I decided for this term based on fact in 2008 a lot of important tax changes came in legal power (for example flat individual income tax). By involving data from the previous years to my model, this can bring certain complication for result’s interpretation.
Even with these simplifications my model is not loosing its relevance. My goals were not involving all the government tools to my model but defining clear rules for setting the government policies.

== Simulation and Modelling ==

For proving the relevance of selected economic tools I used regressive analysis. Then I did Monte Carlo Simulation.

== == Regressive Analysis == ==

Before using Monte Carlo I had to prove the influence of selected tools to the economic performance (GDP). For this purpose I used regressive analysis. The R rate was 0,877068461027525. This proves the tools selected by me have certain impact on the output (not the full one as I will explain later).
I also got coefficients for selected tools representing their contribution to the output. Since the individual income tax rate is still the same since 2008, its coefficient was 0 (based on this tool is not relevant for my future steps). For the other tools I got following coefficients:
Corporate Income Tax Rate = 12994,6878898414
Government Spending = 2,95223111181548
Net Export = 2,79310070627737

== == Monte Carlo Simulation == ==

When I had this done, I did Monte Carlo Simulation. With random numbers generator I generated random possible GDP values. Then I divided these values by the coefficients I got from regressive analysis. Based on this I set the values of all government tools necessary for reaching the selected GDP value.
== == Conclusion == ==
The Monte Carlo simulation helped me to set the ideal values of the government tools for reaching certain level of GDP. This can be used for proposing the government policies enhancing an economic growth.
My simulation also did not prove the principles of neoclassic economics. The situations with the highest GDP were also situations with the highest income tax rates which is a right opposite of the neoclassic economic theory. In these situations the government spending was also the highest, so we can even say my simulation proves more the principles of Keynesian economics.
But this does not mean my simulation totally rejected the neoclassic economics theories. There are just more important factors directly influencing GDP than tax rates. Even the simulation is favouring the high taxes, we can still expect lowering the taxes have positive indirect impact on factors like consumption and investments which have direct impact on GDP but they are not under full control of a government, so they were not included in my simulation. This is also proved by a fact the fact R rate was only 0,877068461027525 (it means there are more factors having impact on GDP growth).
It is also good to realize the sources are not unlimited. With ignoring the other economic facts, my model can lead to an idea that for ensuring GDP growth, you just need to tax people more and spend more money. But the reality is much more difficult. Every government is supposed to behave fiscally responsible, so it has to keep the deficit and public debt under control. The Laffer Curve also proves you cannot raise the tax rate above certain level.

== Source File ==
[http://www.simulace.info/index.php/File:Monte_Carlo-Government_Policies.xlsx Monte Carlo-Government Policies.xlsx]

File:Monte Carlo-Government Policies.xlsx

2018-01-16T23:03:01Z

Xbilr00: File to Monte Carlo Simulation Government Policies' Impact.

File to Monte Carlo Simulation Government Policies' Impact.

Assignments WS 2017/2018

2017-12-16T16:13:12Z

Xbilr00: /* Government Policies and Its Influence to Economy (xbilr00) */

== Simulation Proposal (feld00) ==

I am going to simulate a public transport system. The idea came from travelling around Europe, being surprised how often public transport systems fail in large cities and still they are very expensive. Prague public transport is rare exception. Buses, trams and subway trains arrive with minimal deviation from planned arrival time usually in seconds. I believe that there is sophisticated simulation software behind this.

In order to simplify the task let’s presume that it is not about money. We are not going to optimize costs and incomes. The purpose of this simulation is to optimize:

• Numbers of transportation units (TU) needed

• Frequency of releasing TUs

• their arrival time

All stated above in order to prevent people queueing on public transportation stops and to prevent transportation units from crowding.
Microsoft Excel and SimProcess if needed will be used to perform this simulation.

:: for Monte Carlo or Simprocess you need solid quality hard data - what particular solid resources would you bas the simulation on? In addition I think you simplify it so much into some artificial "Numbers of transportation units", that would make the simulation unusable. I would suggest something less ambitious - spacial simulation(agent based, simprocess) of one type of transportation based on real data, if you find some.[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 15:49, 15 December 2017 (CET)

:::: You are right, maybe I can do less ambitious project. What about evacuation from a building:
:::: It will be a Agent-based simulation model. I will use NetLogo software to build an building enviroment, which will include walls and staff inside. Agents will randomly move around the building. If they colide with a wall they turn different direction. If they colide with a staff member, he will navigate them to the exit. Is that possible?
:::: [[User:feld00|feld00]] ([[User talk:feld00|talk]]) 22:35, 15 December 2017 (CET)

== Simulation Proposal (xvatj00) ==

Software: Vensim

I am a contemporary gospel choir conductor (choir and full professional band). We organize more or less 3 concerts a year. It has been a long time since we released our last CD and now we would like to earn money to be able to start recording a new one. For this purpose, I would like to find out those factors (such as choir performance, band performance, tickets’ price, concert’s location, etc.) that influence potential audience when choosing a band to go see and how to improve them, and thus get more people to come to our concerts - and earn more money for the tickets and in general. I will use a survey to get data about people’s preferences.
[[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 17:45, 27 November 2017 (CET)
::For this kind of simulation you would need ritch historical data so that you would be able to find premises you would then build the equations on (and to be able to verify the model when you compare its results with the historical data). Unfortunately the survey will not help you to quantify the parameters and the number of concerts is really low to be usable for such simulation. I probabbly would suggest a different topic. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 18:43, 30 November 2017 (CET)
:::I can get data up to 10 years back. The number of concerts included only those concert that are organized by us only, but we perform in many other concerts as well. Do you have any suggestions how to make the simulation possible? Thank you. [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 18:59, 30 November 2017 (CET)
::::: You would have to be able to define parameters that determine the demand for the individual concerts, and based on the data quantify them and quantify their impact on the demand for a concert. Based on that one could then discuss how the concert and its content should be se up so that you get maximum profit out of it. That is not a really easy ...[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 15:07, 6 December 2017 (CET)

=== Intersection Optimalization (NEW ASSIGNMENT) ===
Software: NetLogo

Almost every day, I walk by the intersection of Anglická and Bělehradská / Škrétova. During peak hours, there are traffic jams on only one street leading to the intersection, which I find interesting. Because of this fact, I would like to simulate the intersection in order to find out if the lights are really optimally set there, and potentially, find out the optimal setting of the intersection’s lights.

As I’ve already mentioned, there are lights directing the intersection. Also, there is a tram track on the Bělehradská / Škrétova street which goes straight, while most of the cars coming from Bělehradská street turn left. I will use real intervals of all of the lights from a chosen time during peak hours, and the number of cars and trams coming to the intersection (including their speed, direction, etc.). At first, I will set the lights to constant ticks according to the reality to simulate the real situation. After that, I will try to find out an optimal setting of the lights and evaluate, what the optimal setting is or if it meets with the reality. [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 18:48, 8 December 2017 (CET)

: Please, try to obtain real data. '''Approved'''. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 04:05, 12 December 2017 (CET)

== Social media post (Amelievh) ==

Software: Netlogo

Nowadays social media is a hot topic, and a lot of recruiters and other business people use linked in to attract new employees or just to share their thoughts.

For my simulation, I was thinking about researching the reach of a social media post. Someone posts something on LinkedIn, and depending on the amount of connection and amount of sharing I want to check how many people you can reach with one post. I will try to find real-world numbers and make it a useful tool for the business world.

: Simulations on social media are typically problematic, mostly due to the lack of real data. I would recommend to try finding, something else. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 04:11, 12 December 2017 (CET)

'''New proposal: gender pay gap'''

Software: Vensim

The gender pay gap is a difficult problem to solve because it is caused by different reasons (education, age, part-time working ...). These are main reasons, but all these reasons are influenced by other aspects and factors.I want to simulate these different reasons + influences in Vensim and work out the most effective solutions to reduce the pay gap. I would specify on 1 country because data is different per country. Easiest and most interesting for me is Belgium.
:: What particular literature and data will you base it on? [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 12:07, 15 December 2017 (CET)
::: I wrote a paper on this topic for another course wherefore I found a lot of statistical data. The EU publishes statistical data about this topic and reasons for it. I came up with the idea after seeing the Vensim example of SchoolLife which also showed a lot of influence on your future career. Only googling 'Gender Pay Gap Belgium' give you already a lot of publications and statistical information on this topic. --[[User:Amelievh|Amelievh]] ([[User talk:Amelievh|talk]]) 12:20, 15 December 2017 (CET)
:::: OK, '''approved''', but you have to well argument the parameters and equations of the simulation (including the citations to accesable resources) in the report which has to accompany the simulation so that we can verify that it is based on real data and makes sense.

==Simulation Proposal (A_V) ==
Software: NetLogo

We own a zoo. We have a huge kennel for hamsters. We have observed a strange behavior of the hamsters. When a female hamster gives birth to babies (usually up to 12), the mother may come under the pressure of nurturing each and everyone of them. After giving the birth a female hamster becomes weak and may die if does not have enough food and vitamins. Also when the mother is weak, she can not lactate milk for all of her babies. Since the quality of food provided by the zoo does not always satisfy the hamster, the mother eats her weakest babies to get extra protein to feed other babies, which increases the probability of survival of her and the rest babies. Another reason of the deaths of hamsters, as mentioned above, is the adequate quality of food. If the food does not satisfy the hamsters, they do not eat it and the food rots by polluting the kernel which leads to an increased number of hamster deaths.
In the simulation I will focus on how much the food quality, the amount of food and keeping the kernel clean influences the number of hamster deaths.

: Makes sense, however it is necessary to obtain real data. Implementation of some of them will not be easy. '''Approved'''.

==Simulation proposal (hram00) ==
Software: NetLogo

Imagine a beach by the ocean guarded by several lifeguards. The warmer the ocean is, the more jellyfish come. If there is a lot of jellyfish in the water, people often get stung. If they get proper treatment in less then five minutes, the pain goes away quickly end they can enjoy the day on the beach. Otherwise they're mad for the rest of the day. In case someone is alergic, the situation can get critical.
My simulation should serve as a support for decision how many lifeguard should be placed on the beach and how far from each other to provide the best services and ensure the highest satisfaction of people on the beach and make sure no one will die because of jellyfish sting.
The Simulation will be simplified but based on reality. There are no real data about number of jellyfish in the water but there are data about number of people stung every day. Based on current experience I can make a simulation which is close to reality. So far there is one lifeguard each 200 meters, at the begining of the season when the water is cold 70 F there is 0-2 people stung in one lifeguard's area, in the hot days by the end of the season (water has about 85 F) the numbers of people stung on each lifeguard stand go up to 100 a day and we know there are cases that it took too long to get help.

==Hub airport (yaua00) ==
Software: NetLogo

As I study not in my home country I have to use plane quite often to get home and sometimes I have to go to a hub airport and change the plane there. So in my simulation I want to show the phenomenon of hub airports. Hub airports are used by one or more airlines to concentrate passenger traffic and flight operations at a given airport. They serve as transfer (or stop-over) points to get passengers to their final destination. The simulation will start with the certain amount of the airports and airplanes will appear at random locations. Airplanes will find a random airport and fly to it, leaving trails on screen to show their paths. Over time new airport and a new airplane will be built. The airports that have existed for the longest will obviously already have the greatest number of airplanes flying to them, but the goal of the simulation is to see when over some time after new airports are built, if the new airport is going to get more planes and if there is going to be new hub airport. [[User:Yaua00|Yaua00]] ([[User talk:Yaua00|talk]]) 23:21, 12 December 2017 (CET)

==Government Policies and Its Influence to Economy (xbilr00)==
Software: Vensim

I would like to simulate an impact of government decision to a economy. The government will have few tools which can be fully influenced by political decisions (government spending, tax rates etc.). Based on this I will simulate an impact of these decisions to economic indicators (GDP growth, state budget incomes, inflation, state budget saldo etc.). This simulation should reflect a great complexity of each decision and its impact even to indicators which you will not imagine on the first sight.
::This is very complex - the simulation has to make sense so the question is what particular literature and particular models will you base it on? [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 20:46, 14 December 2017 (CET)
:: Ok. So what if only one variable would be a tax rate? I will define the exact rules in a special document.
::::This is pretty complex topic so it cannot be done on just spontaneous basis, you either have to have a reasonable model based on some solid literature, you would base the simulation on, or try something else.[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 15:33, 15 December 2017 (CET)
:::::Ok. My simulation would be based on neoclassical economy which is saying that lowering taxes boosts the economic growth. On the other hand it decreases state budget income but the economic growth should cause a contradictory effect. I would like to prove this theory on real numbers. I decided to focus in on Czech economy. I will use the data published by Czech Statistical Bureau about tax rates, GDP growth and state budget incomes. Of course there will be a little generalization but it should reflect the real trends. Based on this I will build my simulation. Is it ok now or should I rather find something else?
:::::: You can approch it this way, but then it is task for Monte Carlo - find the sensitivity of individual parameters on each other (based on the data and theory you specified) and then create a simulation in Excel. Agreed? [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 12:21, 16 December 2017 (CET)
:::::::Ok. Is it approved from your side? I will probably visit you in January during your consultancy hours.

==Influenza A virus subtype H1N1 (alrw00)==
Software: Netlogo

I would like to simulate the spread of the virus H1N1 via the breathed air in a small isolated population. The model should examine the emergent effects of aspects of a polluted air and human contact. The user controls the population’s tendency to practice abstinence, the amount of time a person in the population will stay healthy. Exploration of the first and second variables may illustrate how changes in human behavior in the isolated population contributes to increases in the prevalence of H1N1 as transmitted diseases, while exploration of the third and fourth may provide contemporary solutions to the problem.

==Rumour has it --[[User:Mashal|Mashal]] ([[User talk:Mashal|talk]]) 23:36, 15 December 2017 (CET)==
Sotware: NetLogo

So, this simulation will be interesting for someone who wants to rule the world (who doesn't?).
This is representation of dictatorial regime. There is one rumour, that can turn down this regime (not by itself, just people will go for revolution), so it's dangerous and government doesn't want it be heard. There are three kinds of agents there: POLICE, PEOPLE and WHISPERERS. Police try to find and catch the whisperers. Whisperers try to tell a rumour to people. The one from people group who hears the rumour becomes a whisperer. If one policeman can't find a whisperer for a long time government kills him (because he is either unprofessional or against the government). If the whole people become whisperers regime will lose. If the police will catch and kill all whisperers regime will win.
I want to see how all this system depends on the number of police, whisperers and people.

== Multilingual community simulation (xlusm05) ==
Software: NetLogo

Linguists are concearned that half of the existing languages will be extinct by the end of the 21 century due to globalization. There are different factors that affect the language’s viability, most importantly: total number of speakers, trends for increase or decrease in the number of speakers, transmission to younger generations, its usage on the level of administration and education or only in informal domestic environment. I would like to create a simulation of a multilingual community where all the above factors are known and then apply this model on real data of a particular country. The goal is to define if some language is endangered and will soon become extinct.

Assignments WS 2017/2018

2017-12-15T17:39:37Z

Xbilr00: /* Government Policies and Its Influence to Economy (xbilr00) */

== Simulation Proposal (feld00) ==

I am going to simulate a public transport system. The idea came from travelling around Europe, being surprised how often public transport systems fail in large cities and still they are very expensive. Prague public transport is rare exception. Buses, trams and subway trains arrive with minimal deviation from planned arrival time usually in seconds. I believe that there is sophisticated simulation software behind this.

In order to simplify the task let’s presume that it is not about money. We are not going to optimize costs and incomes. The purpose of this simulation is to optimize:

• Numbers of transportation units (TU) needed

• Frequency of releasing TUs

• their arrival time

All stated above in order to prevent people queueing on public transportation stops and to prevent transportation units from crowding.
Microsoft Excel and SimProcess if needed will be used to perform this simulation.

:: for Monte Carlo or Simprocess you need solid quality hard data - what particular solid resources would you bas the simulation on? In addition I think you simplify it so much into some artificial "Numbers of transportation units", that would make the simulation unusable. I would suggest something less ambitious - spacial simulation(agent based, simprocess) of one type of transportation based on real data, if you find some.[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 15:49, 15 December 2017 (CET)

== Simulation Proposal (xvatj00) ==

Software: Vensim

I am a contemporary gospel choir conductor (choir and full professional band). We organize more or less 3 concerts a year. It has been a long time since we released our last CD and now we would like to earn money to be able to start recording a new one. For this purpose, I would like to find out those factors (such as choir performance, band performance, tickets’ price, concert’s location, etc.) that influence potential audience when choosing a band to go see and how to improve them, and thus get more people to come to our concerts - and earn more money for the tickets and in general. I will use a survey to get data about people’s preferences.
[[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 17:45, 27 November 2017 (CET)
::For this kind of simulation you would need ritch historical data so that you would be able to find premises you would then build the equations on (and to be able to verify the model when you compare its results with the historical data). Unfortunately the survey will not help you to quantify the parameters and the number of concerts is really low to be usable for such simulation. I probabbly would suggest a different topic. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 18:43, 30 November 2017 (CET)
:::I can get data up to 10 years back. The number of concerts included only those concert that are organized by us only, but we perform in many other concerts as well. Do you have any suggestions how to make the simulation possible? Thank you. [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 18:59, 30 November 2017 (CET)
::::: You would have to be able to define parameters that determine the demand for the individual concerts, and based on the data quantify them and quantify their impact on the demand for a concert. Based on that one could then discuss how the concert and its content should be se up so that you get maximum profit out of it. That is not a really easy ...[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 15:07, 6 December 2017 (CET)

=== Intersection Optimalization (NEW ASSIGNMENT) ===
Software: NetLogo

Almost every day, I walk by the intersection of Anglická and Bělehradská / Škrétova. During peak hours, there are traffic jams on only one street leading to the intersection, which I find interesting. Because of this fact, I would like to simulate the intersection in order to find out if the lights are really optimally set there, and potentially, find out the optimal setting of the intersection’s lights.

As I’ve already mentioned, there are lights directing the intersection. Also, there is a tram track on the Bělehradská / Škrétova street which goes straight, while most of the cars coming from Bělehradská street turn left. I will use real intervals of all of the lights from a chosen time during peak hours, and the number of cars and trams coming to the intersection (including their speed, direction, etc.). At first, I will set the lights to constant ticks according to the reality to simulate the real situation. After that, I will try to find out an optimal setting of the lights and evaluate, what the optimal setting is or if it meets with the reality. [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 18:48, 8 December 2017 (CET)

: Please, try to obtain real data. '''Approved'''. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 04:05, 12 December 2017 (CET)

== Social media post (Amelievh) ==

Software: Netlogo

Nowadays social media is a hot topic, and a lot of recruiters and other business people use linked in to attract new employees or just to share their thoughts.

For my simulation, I was thinking about researching the reach of a social media post. Someone posts something on LinkedIn, and depending on the amount of connection and amount of sharing I want to check how many people you can reach with one post. I will try to find real-world numbers and make it a useful tool for the business world.

: Simulations on social media are typically problematic, mostly due to the lack of real data. I would recommend to try finding, something else. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 04:11, 12 December 2017 (CET)

'''New proposal: gender pay gap'''

Software: Vensim

The gender pay gap is a difficult problem to solve because it is caused by different reasons (education, age, part-time working ...). These are main reasons, but all these reasons are influenced by other aspects and factors.I want to simulate these different reasons + influences in Vensim and work out the most effective solutions to reduce the pay gap. I would specify on 1 country because data is different per country. Easiest and most interesting for me is Belgium.
:: What particular literature and data will you base it on? [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 12:07, 15 December 2017 (CET)
::: I wrote a paper on this topic for another course wherefore I found a lot of statistical data. The EU publishes statistical data about this topic and reasons for it. I came up with the idea after seeing the Vensim example of SchoolLife which also showed a lot of influence on your future career. Only googling 'Gender Pay Gap Belgium' give you already a lot of publications and statistical information on this topic. --[[User:Amelievh|Amelievh]] ([[User talk:Amelievh|talk]]) 12:20, 15 December 2017 (CET)
:::: OK, '''approved''', but you have to well argument the parameters and equations of the simulation (including the citations to accesable resources) in the report which has to accompany the simulation so that we can verify that it is based on real data and makes sense.

==Simulation Proposal (A_V) ==
Software: NetLogo

We own a zoo. We have a huge kennel for hamsters. We have observed a strange behavior of the hamsters. When a female hamster gives birth to babies (usually up to 12), the mother may come under the pressure of nurturing each and everyone of them. After giving the birth a female hamster becomes weak and may die if does not have enough food and vitamins. Also when the mother is weak, she can not lactate milk for all of her babies. Since the quality of food provided by the zoo does not always satisfy the hamster, the mother eats her weakest babies to get extra protein to feed other babies, which increases the probability of survival of her and the rest babies. Another reason of the deaths of hamsters, as mentioned above, is the adequate quality of food. If the food does not satisfy the hamsters, they do not eat it and the food rots by polluting the kernel which leads to an increased number of hamster deaths.
In the simulation I will focus on how much the food quality, the amount of food and keeping the kernel clean influences the number of hamster deaths.

: Makes sense, however it is necessary to obtain real data. Implementation of some of them will not be easy. '''Approved'''.

==Simulation proposal (hram00) ==
Software: NetLogo

Imagine a beach by the ocean guarded by several lifeguards. The warmer the ocean is, the more jellyfish come. If there is a lot of jellyfish in the water, people often get stung. If they get proper treatment in less then five minutes, the pain goes away quickly end they can enjoy the day on the beach. Otherwise they're mad for the rest of the day. In case someone is alergic, the situation can get critical.
My simulation should serve as a support for decision how many lifeguard should be placed on the beach and how far from each other to provide the best services and ensure the highest satisfaction of people on the beach and make sure no one will die because of jellyfish sting.
The Simulation will be simplified but based on reality. There are no real data about number of jellyfish in the water but there are data about number of people stung every day. Based on current experience I can make a simulation which is close to reality. So far there is one lifeguard each 200 meters, at the begining of the season when the water is cold 70 F there is 0-2 people stung in one lifeguard's area, in the hot days by the end of the season (water has about 85 F) the numbers of people stung on each lifeguard stand go up to 100 a day and we know there are cases that it took too long to get help.

==Hub airport (yaua00) ==
Software: NetLogo

As I study not in my home country I have to use plane quite often to get home and sometimes I have to go to a hub airport and change the plane there. So in my simulation I want to show the phenomenon of hub airports. Hub airports are used by one or more airlines to concentrate passenger traffic and flight operations at a given airport. They serve as transfer (or stop-over) points to get passengers to their final destination. The simulation will start with the certain amount of the airports and airplanes will appear at random locations. Airplanes will find a random airport and fly to it, leaving trails on screen to show their paths. Over time new airport and a new airplane will be built. The airports that have existed for the longest will obviously already have the greatest number of airplanes flying to them, but the goal of the simulation is to see when over some time after new airports are built, if the new airport is going to get more planes and if there is going to be new hub airport. [[User:Yaua00|Yaua00]] ([[User talk:Yaua00|talk]]) 23:21, 12 December 2017 (CET)

==Government Policies and Its Influence to Economy (xbilr00)==
Software: Vensim

I would like to simulate an impact of government decision to a economy. The government will have few tools which can be fully influenced by political decisions (government spending, tax rates etc.). Based on this I will simulate an impact of these decisions to economic indicators (GDP growth, state budget incomes, inflation, state budget saldo etc.). This simulation should reflect a great complexity of each decision and its impact even to indicators which you will not imagine on the first sight.
::This is very complex - the simulation has to make sense so the question is what particular literature and particular models will you base it on? [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 20:46, 14 December 2017 (CET)
:: Ok. So what if only one variable would be a tax rate? I will define the exact rules in a special document.
::::This is pretty complex topic so it cannot be done on just spontaneous basis, you either have to have a reasonable model based on some solid literature, you would base the simulation on, or try something else.[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 15:33, 15 December 2017 (CET)
:::::Ok. My simulation would be based on neoclassical economy which is saying that lowering taxes boosts the economic growth. On the other hand it decreases state budget income but the economic growth should cause a contradictory effect. I would like to prove this theory on real numbers. I decided to focus in on Czech economy. I will use the data published by Czech Statistical Bureau about tax rates, GDP growth and state budget incomes. Of course there will be a little generalization but it should reflect the real trends. Based on this I will build my simulation. Is it ok now or should I rather find something else?

==Influenza A virus subtype H1N1 (alrw00)==
Software: Netlogo

I would like to simulate the spread of the virus H1N1 via the breathed air in a small isolated population. The model should examine the emergent effects of aspects of a polluted air and human contact. The user controls the population’s tendency to practice abstinence, the amount of time a person in the population will stay healthy. Exploration of the first and second variables may illustrate how changes in human behavior in the isolated population contributes to increases in the prevalence of H1N1 as transmitted diseases, while exploration of the third and fourth may provide contemporary solutions to the problem.

Assignments WS 2017/2018

2017-12-15T14:08:55Z

Xbilr00: /* Government Policies and Its Influence to Economy (xbilr00) */

Assignments WS 2017/2018

2017-12-14T13:46:23Z

Xbilr00: /* Government Policies and Its Influence to Economy */

== Simulation Proposal (xvatj00) ==

Software: Vensim

I am a contemporary gospel choir conductor (choir and full professional band). We organize more or less 3 concerts a year. It has been a long time since we released our last CD and now we would like to earn money to be able to start recording a new one. For this purpose, I would like to find out those factors (such as choir performance, band performance, tickets’ price, concert’s location, etc.) that influence potential audience when choosing a band to go see and how to improve them, and thus get more people to come to our concerts - and earn more money for the tickets and in general. I will use a survey to get data about people’s preferences.
[[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 17:45, 27 November 2017 (CET)
::For this kind of simulation you would need ritch historical data so that you would be able to find premises you would then build the equations on (and to be able to verify the model when you compare its results with the historical data). Unfortunately the survey will not help you to quantify the parameters and the number of concerts is really low to be usable for such simulation. I probabbly would suggest a different topic. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 18:43, 30 November 2017 (CET)
:::I can get data up to 10 years back. The number of concerts included only those concert that are organized by us only, but we perform in many other concerts as well. Do you have any suggestions how to make the simulation possible? Thank you. [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 18:59, 30 November 2017 (CET)
::::: You would have to be able to define parameters that determine the demand for the individual concerts, and based on the data quantify them and quantify their impact on the demand for a concert. Based on that one could then discuss how the concert and its content should be se up so that you get maximum profit out of it. That is not a really easy ...[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 15:07, 6 December 2017 (CET)

=== Intersection Optimalization (NEW ASSIGNMENT) ===
Software: NetLogo

Almost every day, I walk by the intersection of Anglická and Bělehradská / Škrétova. During peak hours, there are traffic jams on only one street leading to the intersection, which I find interesting. Because of this fact, I would like to simulate the intersection in order to find out if the lights are really optimally set there, and potentially, find out the optimal setting of the intersection’s lights.

As I’ve already mentioned, there are lights directing the intersection. Also, there is a tram track on the Bělehradská / Škrétova street which goes straight, while most of the cars coming from Bělehradská street turn left. I will use real intervals of all of the lights from a chosen time during peak hours, and the number of cars and trams coming to the intersection (including their speed, direction, etc.). At first, I will set the lights to constant ticks according to the reality to simulate the real situation. After that, I will try to find out an optimal setting of the lights and evaluate, what the optimal setting is or if it meets with the reality. [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 18:48, 8 December 2017 (CET)

: Please, try to obtain real data. '''Approved'''. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 04:05, 12 December 2017 (CET)

=== Social media post (Amelievh) ===

Software: Netlogo

Nowadays social media is a hot topic, and a lot of recruiters and other business people use linked in to attract new employees or just to share their thoughts.

For my simulation, I was thinking about researching the reach of a social media post. Someone posts something on LinkedIn, and depending on the amount of connection and amount of sharing I want to check how many people you can reach with one post. I will try to find real-world numbers and make it a useful tool for the business world.

: Simulations on social media are typically problematic, mostly due to the lack of real data. I would recommend to try finding, something else. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 04:11, 12 December 2017 (CET)

==Simulation Proposal (A_V) ==
Software: NetLogo

We own a zoo. We have a huge kennel for hamsters. We have observed a strange behavior of the hamsters. When a female hamster gives birth to babies (usually up to 12), the mother may come under the pressure of nurturing each and everyone of them. After giving the birth a female hamster becomes weak and may die if does not have enough food and vitamins. Also when the mother is weak, she can not lactate milk for all of her babies. Since the quality of food provided by the zoo does not always satisfy the hamster, the mother eats her weakest babies to get extra protein to feed other babies, which increases the probability of survival of her and the rest babies. Another reason of the deaths of hamsters, as mentioned above, is the adequate quality of food. If the food does not satisfy the hamsters, they do not eat it and the food rots by polluting the kernel which leads to an increased number of hamster deaths.
In the simulation I will focus on how much the food quality, the amount of food and keeping the kernel clean influences the number of hamster deaths.

: Makes sense, however it is necessary to obtain real data. Implementation of some of them will not be easy. '''Approved'''.

==Simulation proposal (hram00) ==
Software: NetLogo

Imagine a beach by the ocean guarded by several lifeguards. The warmer the ocean is, the more jellyfish come. If there is a lot of jellyfish in the water, people often get stung. If they get proper treatment in less then five minutes, the pain goes away quickly end they can enjoy the day on the beach. Otherwise they're mad for the rest of the day. In case someone is alergic, the situation can get critical.
My simulation should serve as a support for decision how many lifeguard should be placed on the beach and how far from each other to provide the best services and ensure the highest satisfaction of people on the beach and make sure no one will die because of jellyfish sting.
The Simulation will be simplified but based on reality. There are no real data about number of jellyfish in the water but there are data about number of people stung every day. Based on current experience I can make a simulation which is close to reality. So far there is one lifeguard each 200 meters, at the begining of the season when the water is cold 70 F there is 0-2 people stung in one lifeguard's area, in the hot days by the end of the season (water has about 85 F) the numbers of people stung on each lifeguard stand go up to 100 a day and we know there are cases that it took too long to get help.

==Hub airport (yaua00) ==
Software: NetLogo

As I study not in my home country I have to use plane quite often to get home and sometimes I have to go to a hub airport and change the plane there. So in my simulation I want to show the phenomenon of hub airports. Hub airports are used by one or more airlines to concentrate passenger traffic and flight operations at a given airport. They serve as transfer (or stop-over) points to get passengers to their final destination. The simulation will start with the certain amount of the airports and airplanes will appear at random locations. Airplanes will find a random airport and fly to it, leaving trails on screen to show their paths. Over time new airport and a new airplane will be built. The airports that have existed for the longest will obviously already have the greatest number of airplanes flying to them, but the goal of the simulation is to see when over some time after new airports are built, if the new airport is going to get more planes and if there is going to be new hub airport. [[User:Yaua00|Yaua00]] ([[User talk:Yaua00|talk]]) 23:21, 12 December 2017 (CET)

==Government Policies and Its Influence to Economy (xbilr00)==
Software: Vensim

I would like to simulate an impact of government decision to a economy. The government will have few tools which can be fully influenced by political decisions (government spending, tax rates etc.). Based on this I will simulate an impact of these decisions to economic indicators (GDP growth, state budget incomes, inflation, state budget saldo etc.). This simulation should reflect a great complexity of each decision and its impact even to indicators which you will not imagine on the first sight.

Assignments WS 2017/2018

2017-12-14T13:46:04Z

Xbilr00:

== Simulation Proposal (xvatj00) ==

Software: Vensim

I am a contemporary gospel choir conductor (choir and full professional band). We organize more or less 3 concerts a year. It has been a long time since we released our last CD and now we would like to earn money to be able to start recording a new one. For this purpose, I would like to find out those factors (such as choir performance, band performance, tickets’ price, concert’s location, etc.) that influence potential audience when choosing a band to go see and how to improve them, and thus get more people to come to our concerts - and earn more money for the tickets and in general. I will use a survey to get data about people’s preferences.
[[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 17:45, 27 November 2017 (CET)
::For this kind of simulation you would need ritch historical data so that you would be able to find premises you would then build the equations on (and to be able to verify the model when you compare its results with the historical data). Unfortunately the survey will not help you to quantify the parameters and the number of concerts is really low to be usable for such simulation. I probabbly would suggest a different topic. [[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 18:43, 30 November 2017 (CET)
:::I can get data up to 10 years back. The number of concerts included only those concert that are organized by us only, but we perform in many other concerts as well. Do you have any suggestions how to make the simulation possible? Thank you. [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 18:59, 30 November 2017 (CET)
::::: You would have to be able to define parameters that determine the demand for the individual concerts, and based on the data quantify them and quantify their impact on the demand for a concert. Based on that one could then discuss how the concert and its content should be se up so that you get maximum profit out of it. That is not a really easy ...[[User:Oleg.Svatos|Oleg.Svatos]] ([[User talk:Oleg.Svatos|talk]]) 15:07, 6 December 2017 (CET)

=== Intersection Optimalization (NEW ASSIGNMENT) ===
Software: NetLogo

Almost every day, I walk by the intersection of Anglická and Bělehradská / Škrétova. During peak hours, there are traffic jams on only one street leading to the intersection, which I find interesting. Because of this fact, I would like to simulate the intersection in order to find out if the lights are really optimally set there, and potentially, find out the optimal setting of the intersection’s lights.

As I’ve already mentioned, there are lights directing the intersection. Also, there is a tram track on the Bělehradská / Škrétova street which goes straight, while most of the cars coming from Bělehradská street turn left. I will use real intervals of all of the lights from a chosen time during peak hours, and the number of cars and trams coming to the intersection (including their speed, direction, etc.). At first, I will set the lights to constant ticks according to the reality to simulate the real situation. After that, I will try to find out an optimal setting of the lights and evaluate, what the optimal setting is or if it meets with the reality. [[User:Xvatj00|Xvatj00]] ([[User talk:Xvatj00|talk]]) 18:48, 8 December 2017 (CET)

: Please, try to obtain real data. '''Approved'''. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 04:05, 12 December 2017 (CET)

=== Social media post (Amelievh) ===

Software: Netlogo

Nowadays social media is a hot topic, and a lot of recruiters and other business people use linked in to attract new employees or just to share their thoughts.

For my simulation, I was thinking about researching the reach of a social media post. Someone posts something on LinkedIn, and depending on the amount of connection and amount of sharing I want to check how many people you can reach with one post. I will try to find real-world numbers and make it a useful tool for the business world.

: Simulations on social media are typically problematic, mostly due to the lack of real data. I would recommend to try finding, something else. [[User:Tomáš|Tomáš]] ([[User talk:Tomáš|talk]]) 04:11, 12 December 2017 (CET)

==Simulation Proposal (A_V) ==
Software: NetLogo

We own a zoo. We have a huge kennel for hamsters. We have observed a strange behavior of the hamsters. When a female hamster gives birth to babies (usually up to 12), the mother may come under the pressure of nurturing each and everyone of them. After giving the birth a female hamster becomes weak and may die if does not have enough food and vitamins. Also when the mother is weak, she can not lactate milk for all of her babies. Since the quality of food provided by the zoo does not always satisfy the hamster, the mother eats her weakest babies to get extra protein to feed other babies, which increases the probability of survival of her and the rest babies. Another reason of the deaths of hamsters, as mentioned above, is the adequate quality of food. If the food does not satisfy the hamsters, they do not eat it and the food rots by polluting the kernel which leads to an increased number of hamster deaths.
In the simulation I will focus on how much the food quality, the amount of food and keeping the kernel clean influences the number of hamster deaths.

: Makes sense, however it is necessary to obtain real data. Implementation of some of them will not be easy. '''Approved'''.

==Simulation proposal (hram00) ==
Software: NetLogo

Imagine a beach by the ocean guarded by several lifeguards. The warmer the ocean is, the more jellyfish come. If there is a lot of jellyfish in the water, people often get stung. If they get proper treatment in less then five minutes, the pain goes away quickly end they can enjoy the day on the beach. Otherwise they're mad for the rest of the day. In case someone is alergic, the situation can get critical.
My simulation should serve as a support for decision how many lifeguard should be placed on the beach and how far from each other to provide the best services and ensure the highest satisfaction of people on the beach and make sure no one will die because of jellyfish sting.
The Simulation will be simplified but based on reality. There are no real data about number of jellyfish in the water but there are data about number of people stung every day. Based on current experience I can make a simulation which is close to reality. So far there is one lifeguard each 200 meters, at the begining of the season when the water is cold 70 F there is 0-2 people stung in one lifeguard's area, in the hot days by the end of the season (water has about 85 F) the numbers of people stung on each lifeguard stand go up to 100 a day and we know there are cases that it took too long to get help.

==Hub airport (yaua00) ==
Software: NetLogo

As I study not in my home country I have to use plane quite often to get home and sometimes I have to go to a hub airport and change the plane there. So in my simulation I want to show the phenomenon of hub airports. Hub airports are used by one or more airlines to concentrate passenger traffic and flight operations at a given airport. They serve as transfer (or stop-over) points to get passengers to their final destination. The simulation will start with the certain amount of the airports and airplanes will appear at random locations. Airplanes will find a random airport and fly to it, leaving trails on screen to show their paths. Over time new airport and a new airplane will be built. The airports that have existed for the longest will obviously already have the greatest number of airplanes flying to them, but the goal of the simulation is to see when over some time after new airports are built, if the new airport is going to get more planes and if there is going to be new hub airport. [[User:Yaua00|Yaua00]] ([[User talk:Yaua00|talk]]) 23:21, 12 December 2017 (CET)

==Government Policies and Its Influence to Economy==
Software: Vensim

I would like to simulate an impact of government decision to a economy. The government will have few tools which can be fully influenced by political decisions (government spending, tax rates etc.). Based on this I will simulate an impact of these decisions to economic indicators (GDP growth, state budget incomes, inflation, state budget saldo etc.). This simulation should reflect a great complexity of each decision and its impact even to indicators which you will not imagine on the first sight.