Bayesian Networks for Reliability Engineering (Paperback)

Baoping Cai

ISBN 10: 9811365180 / ISBN 13: 9789811365188

Published by Springer Verlag, Singapore, Singapore, 2020

About this Item

Paperback. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Seller Inventory # 9789811365188

Bibliographic Details

• Title: Bayesian Networks for Reliability Engineering (Paperback)
• Publisher: Springer Verlag, Singapore, Singapore
• Publication Date: 2020
• Language: English
• ISBN 10: 9811365180
• ISBN 13: 9789811365188
• Binding: Paperback
• Condition: new

About this title

Synopsis

 

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.

About the Author

Baoping Cai is an associate professor at the China University of Petroleum (East China), a visiting researcher of the "Hong Kong Scholar" program at the City University of Hong Kong, and a visiting researcher at the Norwegian University of Science and Technology. He is an associate editor of IEEE Access (SCI journal) and Human-Centric Computing and Information Sciences (SCI journal), an editorial board member of 3 international journals, and a leading guest editor of 1 international journal. His research interests include reliability engineering, fault diagnosis, risk analysis, and Bayesian networks methodology and application. Up to now, he has published 65 SCI-index journal papers, 4 monographs, and holds 37 patents.