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Lecturer(s)
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Bikila Dawit Dejene, M.Sc.
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Kopáčková Hana, doc. Ing. Ph.D.
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Čapek Jan, prof. Ing. CSc.
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Course content
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Introduction to process modeling and simulation. Numerical methods used in process simulation. Black box method, gradual derivative method, method of gradual integration Weight sequence, creation of discrete model, difference equation. Moving averages. Box - Jenkins methodology, models AR, MA, ARMA, ARIMA. Evolutionary models of growth. Prey-predator model. Model of chaotic process behavior. Elliot's waves. Discrete Process Simulation, Petri Networks. Agent models. System thinking. System dynamics .
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Skills training
- Preparation of a presentation (report)
- 18 hours per semester
- Contact teaching
- 52 hours per semester
- Preparation for a credit (assessment)
- 10 hours per semester
- Individual project
- 30 hours per semester
- Preparation for an exam
- 20 hours per semester
- Home preparation for classes
- 20 hours per semester
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Learning outcomes
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The aim of the course is to acquire theoretical knowledge in the field of modeling and simulation of social and economic processes using PC as a tool.
A student who has successfully completed the course can: define basic concepts and know their use; characterize processes; choose a suitable model for solving the problem select a suitable simulation program A student who has successfully completed the course know: define the entities and attributes needed for a particular model; define and model process input and output attributes; apply linear and nonlinear computational methods to these attributes to design evolutionary and agent models to simulate dynamic processes control the basic functions of the selected modeling tool use the selected model to address a set goal control the basic functions of the selected simulation program. The student who has successfully completed the course is able to: summarize clearly the views of other team members; to communicate in a clear and convincing way to professionals and lay people information on the nature of professional issues and their own opinion on their solution. Able to interpret simulation experiment results correctly
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Prerequisites
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unspecified
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Assessment methods and criteria
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Oral examination, Written examination
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Recommended literature
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Borschev, A.. The big book of simulation modeling with AnyLogic. Sunny, 2015.
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Sayama, H. Introduction to the modeling and analylisys of complex systems. SUNNY, 2016.
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ZEIGLER, B.,P., PRAEHOFER, H., KIM,t. Theory of modeling and simulation. Academic Press London., 2000.
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