|Name||Fundamentals of Computer Simulation and Modelling|
|Status||Compulsory/Courses of Limited Choice|
|Level and type||Undergraduate Studies, Academic|
|Field of study||Computer Science|
|Faculty||Department of Modelling and Simulation|
|Academic staff||Gaļina Merkurjeva, Jana Bikovska, Jurijs Merkurjevs, Jeļena Pečerska, Raisa Smirnova, Vitālijs Boļšakovs|
|Credit points||3.0 (4.5 ECTS)|
The module ‘Fundamentals of System Modelling and Simulation’ considers fundamental concepts of system modelling, i.e. the concept of computer modelling and standard procedure, modelling motivation and main principles, and model development and application aspects. The module discusses the essential principles of analytical modelling and types of analytical models used in practice, such as differential equations, difference equations, Boolean functions, logical expressions, finite automats, network models and Petri nets. The fundamentals and applications of system statistical modelling are considered. The structure of a computer simulation model and its main components are defined. Discrete event simulation methods for input modelling, time handling and process simulation, simulation on spreadsheets and simulation output analysis are considered. Systems dynamics approach is discussed. Main principles and methods for model testing and validation are given. Software modelling and add-on tools are reviewed..
Goals and objectives
of the course in terms
of competences and skills
|Competences and skills demonstrated: knowledge of basic concepts of system modelling, model design and application aspects, a model taxonomy, analytical models, main principles and methods of system computer simulation; ability to define requirements to a system model and identify its most appropriate type; use simulation software to design a system simulation model in order to apply it to system analysis and optimisation.|
Is able to interpret and use system modelling terminology. - Successfully passed e-test on system modelling basic concepts.
Is able to interpret and use analytical models of complex systems. - Successfully passed e-test on analytical modelling. Using MATLAB, demonstrated ability to apply analytical models to modelling and analysis of a control system.
Is able to interpret and use system statistical (simulation) techniques. - Successfully passed e-test on application aspects of system statistical modelling. Demonstrated ability to use simulation techniques (Course project).
Is able to develop simple simulation models and use them in order to analyse and improve system behaviour. - Using ProModel software, demonstrated ability to develop ProModel-based simulation models and apply them to system analysis and optimisation.
Is able to identify an appropriate model type for a specific problem. - Successfully passed e-test based on problem analysis and selection of an appropriate model.
Is able to describe different analytical and algorithmic models and their application aspects in system modelling, analysis and optimisation. - Demonstrated ability to identify a specific subject and provide a reasoned explanation (Course exam).
|Course prerequisites||Basic knowledge in mathematics, discrete mathematics, probability theory and mathematical statistics.|