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Estimation of rare event probabilities in complex aerospace and other systems : a practical approach /

Comprehensive and insightful, this valuable resource offers a broad up-to-date view of techniques to estimate rare event probabilities, described with a unified notation to ease implementation plus a spectrum of simulation results on academic and realistic use cases. --

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Morio, J�er�ome, 1983- (Autor), Balesdent, Mathieu, 1985- (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Woodhead Publishing is an imprint of Elsevier, [2016]
Colección:Woodhead Publishing in mechanical engineering ; no. 720.
Temas:
Acceso en línea:Texto completo

MARC

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100 1 |a Morio, J�er�ome,  |d 1983-  |e author. 
245 1 0 |a Estimation of rare event probabilities in complex aerospace and other systems :  |b a practical approach /  |c J�er�ome Morio and Mathieu Balesdent. 
264 1 |a Amsterdam :  |b Woodhead Publishing is an imprint of Elsevier,  |c [2016] 
264 4 |c �2016 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Woodhead publishing in mechanical engineering ;  |v number 720 
588 0 |a Online resource; title from PDF title page (EBSCO, viewed November 25, 2015) 
504 |a Includes bibliographical references and index. 
505 0 |a Front Cover; Estimation of Rare Event Probabilities in Complex Aerospace and Other Systems: A Practical Approach; Copyright; Dedication; Contents; Preface; Foreword; Biography of the external contributors to this book; Abbreviations; Chapter 1: Introduction to rare event probability estimation; 1.1 The book purposes; 1.2 What are the events of interest considered in this book?; 1.3 The book organization; References; Part One: Essential Background in Mathematics and System Analysis; Chapter 2: Basics of probability and statistics; 2.1 Probability theory operators; 2.1.1 Elements of vocabulary 
505 8 |a 2.1.2 Notion of dependence of random events andconditional probabilities 2.1.3 Continuous random variables; 2.1.3.1 Definitions; 2.1.3.2 Parameters of continuous random variables; 2.1.4 Continuous multivariate random variables; 2.1.4.1 Definitions and theorems; 2.1.4.2 Dependence of multivariate random variables ; 2.1.5 Point estimation ; 2.2 Random variable modeling; 2.2.1 Overview of common probability distributions; 2.2.1.1 Univariate distributions; Uniform distribution; Exponential distribution; Gaussian distribution; Truncated Gaussian distribution; Log-normal distribution 
505 8 |a Cauchy distributionChi-squared distribution; Gamma and beta distributions; Laplace distribution; Some properties of univariate distributions; 2.2.1.2 Multivariate distributions; Multivariate normal distribution; 2.2.2 Kernel-based laws; 2.3 Convergence theorems and sampling algorithms; 2.3.1 Strong law of large numbers ; 2.3.2 Central limit theorem ; 2.3.3 Simulation of complex laws using the Metropolis-Hastings algorithm; 2.3.3.1 Markov chain; 2.3.3.2 Some properties of transition kernels; 2.3.3.3 The Metropolis-Hastings algorithm ; 2.3.3.4 Transformation of random variables; References 
505 8 |a Chapter 3: The formalism of rare event probability estimation in complex systems3.1 Input-output system; 3.1.1 Description; 3.1.2 Formalism; 3.2 Time-variant system; 3.2.1 Description; 3.2.2 Formalism; 3.3 Characterization of a probability estimation; References; Part Two: Practical Overview of the Main Rare Event EstimationTechniques; Chapter 4: Introduction; 4.1 Categories of estimation methods; 4.2 General notations; 4.3 Description of the toy cases; 4.3.1 Identity function; 4.3.2 Polynomial square root function; 4.3.3 Four-branch system; 4.3.4 Polynomial product function; References 
505 8 |a Chapter 5: Simulation techniques5.1 Crude Monte Carlo; 5.1.1 Principle; 5.1.2 Application on a toy case; Four-branch system; 5.1.3 Conclusion; 5.2 Simple variance reduction techniques; 5.2.1 Quasi-Monte Carlo; 5.2.2 Conditional Monte Carlo; 5.2.2.1 Principle; 5.2.2.2 Conclusion; 5.2.3 Control variates; 5.2.3.1 Principle; 5.2.3.2 Application on a toy case; Four-branch system; 5.2.3.3 Conclusion; 5.2.4 Antithetic variates; 5.2.4.1 Principle; 5.2.4.2 Application to a toy case; Identity function; 5.2.4.3 Conclusion; 5.3 Importance sampling; 5.3.1 Principle of importance sampling 
520 |a Comprehensive and insightful, this valuable resource offers a broad up-to-date view of techniques to estimate rare event probabilities, described with a unified notation to ease implementation plus a spectrum of simulation results on academic and realistic use cases. --  |c Edited summary from book. 
650 0 |a Engineering  |x Statistical methods. 
650 0 |a Engineering mathematics. 
650 0 |a Aerospace engineering. 
650 0 |a Reliability (Engineering) 
650 6 |a Ing�enierie  |x M�ethodes statistiques.  |0 (CaQQLa)201-0022660 
650 6 |a Math�ematiques de l'ing�enieur.  |0 (CaQQLa)201-0021991 
650 6 |a A�erospatiale (Ing�enierie)  |0 (CaQQLa)201-0277933 
650 6 |a Fiabilit�e.  |0 (CaQQLa)201-0026464 
650 7 |a aerospace engineering.  |2 aat  |0 (CStmoGRI)aat300054478 
650 7 |a aeronautical engineering.  |2 aat  |0 (CStmoGRI)aat300162449 
650 7 |a MATHEMATICS  |x Applied.  |2 bisacsh 
650 7 |a MATHEMATICS  |x Probability & Statistics  |x General.  |2 bisacsh 
650 7 |a Aerospace engineering.  |2 fast  |0 (OCoLC)fst00798623 
650 7 |a Engineering mathematics.  |2 fast  |0 (OCoLC)fst00910601 
650 7 |a Engineering  |x Statistical methods.  |2 fast  |0 (OCoLC)fst00910415 
650 7 |a Reliability (Engineering)  |2 fast  |0 (OCoLC)fst01093646 
650 7 |a Probabilitats.  |2 lemac 
650 7 |a Enginyeria industrial  |x �Mtodes esta�dstics.  |2 lemac 
700 1 |a Balesdent, Mathieu,  |d 1985-  |e author. 
776 0 8 |c Original  |z 9780081000915  |z 008100091X  |w (OCoLC)907204598 
830 0 |a Woodhead Publishing in mechanical engineering ;  |v no. 720. 
856 4 0 |u https://sciencedirect.uam.elogim.com/science/book/9780081000915  |z Texto completo