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Bayesian networks in fault diagnosis...

Cai, Baoping.

Bayesian networks in fault diagnosispractice and application /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Bayesian networks in fault diagnosiseditors, Baoping Cai ... [et al.]
Reminder of title:	practice and application /
other author:	Cai, Baoping.
Published:	Singapore :World Scientific,c2019.
Description:	1 online resource (418 p.) :ill. (some col.)
Subject:	Bayesian statistical decision theoryData processing.
Online resource:	https://www.worldscientific.com/worldscibooks/10.1142/11021#t=toc
ISBN:	9789813271494$q(electronic bk.)

Bayesian networks in fault diagnosispractice and application /
Bayesian networks in fault diagnosispractice and application /[electronic resource] :editors, Baoping Cai ... [et al.] - 1st ed. - Singapore :World Scientific,c2019. - 1 online resource (418 p.) :ill. (some col.)

Includes bibliographical references and index.

"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."--

Electronic reproduction.
Singapore :
World Scientific,
[2018]

Mode of access: World Wide Web.

ISBN: 9789813271494$q(electronic bk.)Subjects--Topical Terms:

199283
Bayesian statistical decision theory
--Data processing.

LC Class. No.: QA279.5 / .B39 2019

Dewey Class. No.: 519.542

Bayesian networks in fault diagnosispractice and application /
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020 $z 9789813271876$q(pbk.)
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020 $z 9789813271487$q(hbk.)
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041 0 $a eng
050 0 4 $a QA279.5 $b .B39 2019
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245 0 0 $a Bayesian networks in fault diagnosis $h [electronic resource] : $b practice and application / $c editors, Baoping Cai ... [et al.]
250 $a 1st ed.
260 $a Singapore : $b World Scientific, $c c2019.
300 $a 1 online resource (418 p.) : $b ill. (some col.)
504 $a Includes bibliographical references and index.
520 $a "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."-- $c Publisher's website.
533 $a Electronic reproduction. $b Singapore : $c World Scientific, $d [2018]
538 $a Mode of access: World Wide Web.
588 $a Description based on online resource; title from PDF title page (viewed August 30, 2018)
650 0 $a Bayesian statistical decision theory $x Data processing. $3 199283
650 0 $a Fault location (Engineering) $3 266155
650 0 $a Neural networks (Computer science) $3 181982
650 0 $a Electronic books. $3 242495
700 1 $a Cai, Baoping. $3 840196
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/11021#t=toc