Course code InfT3025
Credit points 3
Basics of Computer Experiments
Total Hours in Course81
Number of hours for lectures16
Number of hours for laboratory classes16
Independent study hours49
Date of course confirmation16.01.2013
Responsible UnitInstitute of Computer Systems and Data Science
Course developer
Ilona Odziņa
Mg. sc. ing.
Course abstract
To simulate a physical system, one needs to create mathematical models to represent physical behavior in various circumstances. For successful test of models is necessary well prepared teaching data set, therefore in this course foreseen to explore methods of computer experiment design (Latin Hypercube Sampling un Uniform design methods). The models of the real systems are difficult, therefore will be examined optimization methods for structure of models.
Learning outcomes and their assessment
• Knowledge – of the linear, nonlinear, stohastic computer experiments planning methods, as well as the real system model optimization methods.
• Skills – to take computer experiment planning and real system model optimization using linear, nonlinear and stohastic methods, which are mentioned in programm.
• Competence – appropriate selection of methods for planning computer experiments and taking real system model optimization.
Compulsory reading
1. Fang K., Li R., Sudjianto A. Design and modeling for computer eksperiments. London: Chapman & Hall/CRC, 2006. 290 p.
2. Online Statistics Education: An Interactive Multimedia Course of Study. [tiešsaiste]. [skatīts 30.01.2013.] Pieejams: http://onlinestatbook.com/2/index.html
Further reading
1. Sacks J., Welch W.J., Mitchell T.J., and Wynn H.P. Design and analysis of computer experiments. Statistical Science, 1989. 435 p.
[skatīts 11.02.2013.] Pieejams: http://www.stat.osu.edu/~comp_exp/jour.club/Sacks89.pdf
2. Engineering Statistical Handbook. [tiešsaiste]. [skatīts 30.01.2013.] Pieejams: http://www.itl.nist.gov/div898/handbook/pri/section3/pri3.htm