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ISBN 10: 9813271485 ISBN 13: 9789813271487
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Published by World Scientific Publishing Company, 2018
ISBN 10: 9813271485 ISBN 13: 9789813271487
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Published by World Scientific Pub Co Inc, 2018
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Published by World Scientific Pub Co Inc, 2018
ISBN 10: 9813271485 ISBN 13: 9789813271487
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Published by World Scientific Pub Co Inc, 2018
ISBN 10: 9813271485 ISBN 13: 9789813271487
Language: English
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Published by World Scientific Pub Co Inc, 2018
ISBN 10: 9813271485 ISBN 13: 9789813271487
Language: English
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Published by World Scientific Pub Co Inc, 2018
ISBN 10: 9813271485 ISBN 13: 9789813271487
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Published by World Scientific Pub Co Inc, 2018
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Published by World Scientific Pub Co Inc, 2018
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Published by World Scientific Pub Co Inc, 2018
ISBN 10: 9813271485 ISBN 13: 9789813271487
Language: English
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Add to basketGebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnFault 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 incr.
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Add to basketBuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.