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Bayesian Networks for Reliability Engineering (Hardcover, 1st ed. 2020): Baoping Cai, Yonghong Liu, Zengkai Liu, Yuanjiang... Bayesian Networks for Reliability Engineering (Hardcover, 1st ed. 2020)
Baoping Cai, Yonghong Liu, Zengkai Liu, Yuanjiang Chang, Lei Jiang
R4,371 Discovery Miles 43 710 Ships in 10 - 15 working days

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.

Bayesian Networks In Fault Diagnosis: Practice And Application (Hardcover): Baoping Cai, Yonghong Liu, Jinqiu Hu, Zengkai Liu,... Bayesian Networks In Fault Diagnosis: Practice And Application (Hardcover)
Baoping Cai, Yonghong Liu, Jinqiu Hu, Zengkai Liu, Shengnan Wu, …
R3,958 Discovery Miles 39 580 Ships in 10 - 15 working days

Fault diagnosis is useful for technicians to detect, isolate, identify faults, and troubleshoot. Bayesian network (BN) is a probabilistic graphical model that effectively deals with various uncertainty problems. This model is increasingly utilized in fault diagnosis.This unique compendium presents bibliographical review on the use of BNs in fault diagnosis in the last decades with focus on engineering systems. Subsequently, eleven important issues in BN-based fault diagnosis methodology, such as BN structure modeling, BN parameter modeling, BN inference, fault identification, validation, and verification are discussed in various cases.Researchers, professionals, academics and graduate students will better understand the theory and application, and benefit those who are keen to develop real BN-based fault diagnosis system.

Bayesian Networks for Reliability Engineering (Paperback, 1st ed. 2020): Baoping Cai, Yonghong Liu, Zengkai Liu, Yuanjiang... Bayesian Networks for Reliability Engineering (Paperback, 1st ed. 2020)
Baoping Cai, Yonghong Liu, Zengkai Liu, Yuanjiang Chang, Lei Jiang
R4,348 Discovery Miles 43 480 Ships in 10 - 15 working days

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.

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