Applications are drawn from water resources, environmental, industrial and other engineering areas. Topics discussed and papers reviewed are selected at the first meeting. Throughout the semester, students make a one-hour presentation of their chosen paper. This is followed by a one and one-half hour discussion, critique, evaluation, and conclusions regarding the topic and its exposition. Students are expected to read every paper before it is presented.
Class size is limited.
The process of stochastic model building including model identification, estimation, and model diagnostic checking. Topics determined by student and faculty interests. Topics may include model and simulation theory, validation, experiment design, output analysis, variance-reduction techniques, simulation optimization, perturbation analysis, parallel and distributed simulation, intelligent simulation systems, animation and output visualization. Course links material from optimization, intelligence systems, and complexity analysis. Formal development of the methods and complete discussion of applications, theoretical properties, and evaluation.