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Synopsis
Weighted Monte Carlo algorithms are extremely useful when direct simulation techniques are inapplicable or ineffective. The methods presented in this book help to minimize computer time and memory required in constructing statistical models for systems described by integral equations.
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Optimization of Weighted Monte Carlo Methods (Scientific Computation)
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Springer Berlin Heidelberg 1992-01-01, 1992
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Optimization of Weighted Monte Carlo Methods (Scientific Computation)
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Optimization of Weighted Monte Carlo Methods
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Springer Berlin Heidelberg, 2011
ISBN 10: 3642759831
ISBN 13: 9783642759833
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The Monte Carlo method is based on the munerical realization of natural or artificial models of the phenomena under considerations. In contrast to classical computing methods the Monte Carlo efficiency depends weakly on the dimen sion and geometric details of the problem. The method is used for solving complex problems of the radiation transfer theory, turbulent diffusion, chemi cal kinetics, theory of rarefied gases, diffraction of waves on random surfaces, etc. The Monte Carlo method is especially effective when using multi-processor computing systems which allow many independent statistical experiments to be simulated simultaneously. The weighted Monte Carlo estimates are constructed in order to diminish errors and to obtain dependent estimates for the calculated functionals for different values of parameters of the problem, i.e., to improve the functional dependence. In addition, the weighted estimates make it possible to evaluate special functionals, for example, the derivatives with respect to the parameters. There are many works concerned with the development of the weighted estimates. In Chap. 1 we give the necessary information about these works and present a set of illustrations. The rest of the book is devoted to the solution of a series of mathematical problems related to the optimization of the weighted Monte Carlo estimates. Seller Inventory # 9783642759833
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Optimization of Weighted Monte Carlo Methods
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Springer Berlin Heidelberg, 2011
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Optimization of Weighted Monte Carlo Methods
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Optimization of Weighted Monte Carlo Methods (Scientific Computation)
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Springer Berlin Heidelberg, 2012
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Optimization of Weighted Monte Carlo Methods
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Optimization of Weighted Monte Carlo Methods
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Springer Berlin Heidelberg, Springer Berlin Heidelberg Nov 2011, 2011
ISBN 10: 3642759831
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The Monte Carlo method is based on the munerical realization of natural or artificial models of the phenomena under considerations. In contrast to classical computing methods the Monte Carlo efficiency depends weakly on the dimen sion and geometric details of the problem. The method is used for solving complex problems of the radiation transfer theory, turbulent diffusion, chemi cal kinetics, theory of rarefied gases, diffraction of waves on random surfaces, etc. The Monte Carlo method is especially effective when using multi-processor computing systems which allow many independent statistical experiments to be simulated simultaneously. The weighted Monte Carlo estimates are constructed in order to diminish errors and to obtain dependent estimates for the calculated functionals for different values of parameters of the problem, i.e., to improve the functional dependence. In addition, the weighted estimates make it possible to evaluate special functionals, for example, the derivatives with respect to the parameters. There are many works concerned with the development of the weighted estimates. In Chap. 1 we give the necessary information about these works and present a set of illustrations. The rest of the book is devoted to the solution of a series of mathematical problems related to the optimization of the weighted Monte Carlo estimates.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 244 pp. Englisch. Seller Inventory # 9783642759833
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Optimization of Weighted Monte Carlo Methods
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Optimization of Weighted Monte Carlo Methods (Scientific Computation)
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