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Computer based modelling and simulation

2. Modelling and simulation with probability and throwing dice

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Abstract

Most systems involve parameters and variables, which are random variables due to uncertainties. Probabilistic methods are powerful in modelling such systems. In this second part, we describe probabilistic models and Monte Carlo simulation along with ‘classical’ matrix methods and differential equations as most real situations are complex (with several variables) and involve uncertainties.

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Suggested Reading

  1. Web Based Simulation,Simulation Journal, Special Issue, Published by International Society for Computer Simulation, San Diego, July, 1999

  2. J Banks (Editor),Handbook of Simulation, John Wiley, 1998.

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Authors and Affiliations

  1. Centre for Aeronautical System Studies and Analyses, DRDO, 560075, Bangalore, India

    N. K. Srinivasan (Director)

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  1. N. K. Srinivasan
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Correspondence to N. K. Srinivasan.

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Srinivasan, N.K. Computer based modelling and simulation. Reson 6, 69–77 (2001). https://doi.org/10.1007/BF02994595

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  • DOI: https://doi.org/10.1007/BF02994595

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