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Joint application ofthe Monte Carlomethod andcomputationalprobabilisticanalysis in problemsof numerical modelingwith datauncertainties Dobronets BorisPopova Olga2024 год

Joint application of the Monte Carlo method and computational probabilistic analysis in problems of numerical modeling with data uncertainties : научное издание
статья из журнала

Дополнительные ссылки: eLibrary
База данных: Каталог библиотеки СФУ
Библиографическое описание: Joint application of the Monte Carlo method and computational probabilistic analysis in problems of numerical modeling with data uncertainties : научное издание / B. B. Dobronets, O. O. Popova. - Текст : непосредственный // Monte Carlo Methods and Applications. - 2024. - Т. 0, № . - ISSN 0929-9629. - ISSN 1569-3961, DOI 10.1515/mcma-2024-2006.
Аннотация: <jats:title>Abstract</jats:title> <jats:p>In this paper, we suggest joint application of computational probabilistic analysis and the Monte Carlo method for numerical stochastic modeling problems. We use all the capabilities of computational probabilistic analysis while maintaining all the advantages of the Monte Carlo method. Our approach allows us to efficiently implement a computational hybrid scheme. In this way, we reduce the computation time and present the results in the form of distributions. The crucial new points of our method are arithmetic operations on probability density functions and procedures for constructing on the probabilistic extensions. Relying on specific numerical examples of solving systems of linear algebraic equations with random coefficients, we present the advantages of our approach.</jats:p>
Год издания: 2024
Авторы: Dobronets Boris , Popova Olga
Издательство: Brill Academic Publishers
Источник: Monte Carlo Methods and Applications
Выпуск: Т. 0
Держатель оригинала документа: Institute of Space and Information Technology, Siberian Federal University, Krasnoyarsk, Russia
Количество экземпляров:
Твёрдая копия издания отсутствует в фонде библиотеки

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