Computer Aided Modelling and Simulation
Mathematical models and modelling generalities; Model-building methodology for difference and differential equations; Model-building methodology for partial differential equations; Methodology for model information storage and integration; Support languages for model simulation; Hardware trends and their impact on simulation; Simulation systems and architectures arising from methodological research.
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Introduction and outline
Mathematical models and modelling generalities
Modelbuilding methodology for difference and differential equations
7 other sections not shown
activities algorithm applicable approach approximation auxiliary model basic behaviour chapter components concepts considered covariance matrix decomposition defined definition derived developed diffusion equation dimensions discrete event discussed distributed entity structure error example experimental frame field finite flux FORTRAN function given identifiability ILLIAC IV implementation input segment instrumental variable interactive iterative Laplace's equation linear mathematical model matrix maximum likelihood method model formalism model-building nodes noise obtained operations ordinary differential equations parallel data parameter estimation partial differential equations pipeline potential principles priori knowledge problem procedure processing elements processor properties real system real-world system recursive representation reservoir sample schemes Section SIMSCRIPT simulation language solution space spatial hierarchy specific static structure STATION structure characterization subroutines techniques theory tion validity values vector vector processors von Neumann architecture zero
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