000			02233cam a2200301zu 4500
001			88914874
003			FRCYB88914874
005			20250107234457.0
006			m o d
007			cr un
008			250108s2019 fr | o|||||0|0|||eng d
020			_a9780128165140
035			_aFRCYB88914874
040			_aFR-PaCSA _ben _c _erda
100	1		_aSamui, Pijush
245	0	1	_aHandbook of Probabilistic Models _c['Samui, Pijush', 'Bui, Dieu Tien', 'Chakraborty, Subrata']
264		1	_bElsevier Science _c2019
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aSamui, Pijush
700	0		_aBui, Dieu Tien
700	0		_aChakraborty, Subrata
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88914874 _qtext/html _a
520			_aHandbook 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
999			_c74163 _d74163