Handbook of Probabilistic Models (Paperback)

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.

General

Imprint:	Butterworth-Heinemann
Country of origin:	United States
Release date:	October 2019
First published:	2020
Editors:	Pijush Samui • Dieu Tien Bui • Subrata Chakraborty • Ravinesh Deo
Dimensions:	229 x 152 x 36mm (L x W x T)
Format:	Paperback
Pages:	590
ISBN-13:	978-0-12-816514-0
Categories:	Books > Professional & Technical > Civil engineering, surveying & building > General Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Computing & IT > Applications of computing > Databases > General
LSN:	0-12-816514-6
Barcode:	9780128165140

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