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Bayesian Networks In Fault Diagnosis: Practice And Application
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Bayesian Networks In Fault Diagnosis: Practice And Application

Book Details

Format Hardback or Cased Book
ISBN-10 9813271485
ISBN-13 9789813271487
Publisher World Scientific Publishing Co Pte Ltd
Imprint World Scientific Publishing Co Pte Ltd
Country of Manufacture GB
Country of Publication GB
Publication Date Oct 16th, 2018
Print length 420 Pages
Product Classification: Bayesian inference
Ksh 25,200.00 Werezi Extended Catalogue

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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.

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.


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