Handbook of Probabilistic Models by Pijush Samui 

Handbook of Probabilistic Models by Pijush Samui

Publisher: Elsevier Butterworth Heinemann

Print ISBN: 9780128165140, 0128165146

eText ISBN: 9780128165461, 0128165464

Copyright year: 2020

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