Handbook of Probabilistic Models carefully examines the application of advanced probabilistic models in conventional engineering fields. In this comprehensive handbook, practitioners, researchers and scientists will find detailed explanations of technical concepts, applications of the proposed methods, and the respective scientific approaches needed to solve the problem. This book provides an interdisciplinary approach that creates advanced probabilistic models for engineering fields, ranging from conventional fields of mechanical engineering and civil engineering, to electronics, electrical, earth sciences, climate, agriculture, water resource, mathematical sciences and computer sciences. Specific topics covered include minimax probability machine regression, stochastic finite element method, relevance vector machine, logistic regression, Monte Carlo simulations, random matrix, Gaussian process regression, Kalman filter, stochastic optimization, maximum likelihood, Bayesian inference, Bayesian update, kriging, copula-statistical models, and more. – Explains the application of advanced probabilistic models encompassing multidisciplinary research- Applies probabilistic modeling to emerging areas in engineering- Provides an interdisciplinary approach to probabilistic models and their applications, thus solving a wide range of practical problems
Dieu Tien Bui & Subrata Chakraborty
Handbook of Probabilistic Models [EPUB ebook]
Handbook of Probabilistic Models [EPUB ebook]
Achetez cet ebook et obtenez-en 1 de plus GRATUITEMENT !
Langue Anglais ● Format EPUB ● ISBN 9780128165461 ● Éditeur Dieu Tien Bui & Subrata Chakraborty ● Maison d’édition Elsevier Science ● Publié 2019 ● Téléchargeable 3 fois ● Devise EUR ● ID 6915438 ● Protection contre la copie Adobe DRM
Nécessite un lecteur de livre électronique compatible DRM