Overview
- Provides a detailed review of the BN-based reliability methodologies
- Presents important theoretical methods for BN-based reliability
- Uses 12 practical engineering cases to illustrate the proposed methods
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Table of contents (11 chapters)
Keywords
About this book
This book presents a bibliographical review of the use of Bayesian networks in reliability over the last decade. Bayesian network (BN) is considered to be one of the most powerful models in probabilistic knowledge representation and inference, and it is increasingly used in the field of reliability. After focusing on the engineering systems, the book subsequently discusses twelve important issues in the BN-based reliability methodologies, such as BN structure modeling, BN parameter modeling, BN inference, validation, and verification. As such, it is a valuable resource for researchers and practitioners in the field of reliability engineering.
Authors and Affiliations
About the authors
Bibliographic Information
Book Title: Bayesian Networks for Reliability Engineering
Authors: Baoping Cai, Yonghong Liu, Zengkai Liu, Yuanjiang Chang, Lei Jiang
DOI: https://doi.org/10.1007/978-981-13-6516-4
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2020
Hardcover ISBN: 978-981-13-6515-7Published: 08 March 2019
Softcover ISBN: 978-981-13-6518-8Published: 14 August 2020
eBook ISBN: 978-981-13-6516-4Published: 28 February 2019
Edition Number: 1
Number of Pages: IX, 257
Number of Illustrations: 28 b/w illustrations, 125 illustrations in colour
Topics: Computational Intelligence, Quality Control, Reliability, Safety and Risk, Power Electronics, Electrical Machines and Networks, Simulation and Modeling