N. N. Olenev 05.2002 p. 1-15, language: английский  Аннотация This paper presents modeling and simulation techniques for complex systems as life support systems. We use a model instead of real things to understand something about that thing. Provided that models are adequate enough descriptions of causal relationship in reality (they are valid), experimenting with them by computer (simulating of reality) can save money, woes and quite often time. Computer simulation is the discipline of designing a model of a studied object, executing the model on a digital computer, and analyzing the execution output. The knowledge base of data contains coordinated determination of the model external variables and parameters and information regarding model expected behavior. The first hardest problem in simulation is determining the exact method to use for creating a model. The paper presents a review on techniques used in model design (conceptual, declarative, functional, constraint, and multi), techniques used in simulation model execution (serial and parallel discrete-event simulation), and techniques used in simulation model analysis (calibration, validation, verification, goal-seeking).  Ключевые слова Model design, discrete-event simulation, parallel and distributed simulation, calibration, validation, validation knowledge base, verification, identification, coefficient of correlation, inequality index, feasible goals method, web-based simulation