Handbook of probabilistic models

Samui, Pijush and Bui, Dieu Tien and Chakraborty, Subrata and Deo, Ravinesh C., eds. (2020) Handbook of probabilistic models. Elsevier (Butterworth-Heinemann), Oxford, United Kingdom. ISBN 978-0-12-816514-0

Abstract

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.


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Item Type: Book (Commonwealth Reporting Category A)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Front Matter, in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sept 2019 -)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sept 2019 -)
Date Deposited: 22 Oct 2019 23:34
Last Modified: 23 Oct 2019 01:53
Uncontrolled Keywords: probabilistic models; engineering
Fields of Research : 01 Mathematical Sciences > 0104 Statistics > 010404 Probability Theory
09 Engineering > 0999 Other Engineering > 099999 Engineering not elsewhere classified
URI: http://eprints.usq.edu.au/id/eprint/37219

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