大葉大學圖書館 |

Language: English

Back

Bayesian networks in fault diagnosis...

Cai, Baoping.

Bayesian networks in fault diagnosis[electronic resource] :practice and application /

Record Type:	Electronic resources : Monograph/item
[NT 15000414]:	519.542
Title/Author:	Bayesian networks in fault diagnosis : practice and application // editors, Baoping Cai ... [et al.]
other author:	Cai, Baoping.
Published:	Singapore : : World Scientific,, c2019.
Description:	1 online resource (418 p.) : : ill. (some col.)
Subject:	Bayesian statistical decision theory - Data processing.
Subject:	Fault location (Engineering)
Subject:	Neural networks (Computer science)
Subject:	Electronic books.
ISBN:	9789813271494
[NT 15000227]:	Includes bibliographical references and index.
[NT 15000229]:	"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."--
Online resource:	https://www.worldscientific.com/worldscibooks/10.1142/11021#t=toc

Bayesian networks in fault diagnosis[electronic resource] :practice 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: 9789813271494Subjects--Topical Terms:

558567
Bayesian statistical decision theory
--Data processing.

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

Dewey Class. No.: 519.542

Bayesian networks in fault diagnosis[electronic resource] :practice and application /
LDR:02036cmm a2200325 a 4500 001 490903
003 WSP
005 2018830064357.2
006 m o d
007 cr cnu---unuuu
008 210127s2019 si a ob 001 0 eng d
020 $a 9789813271494 $q (electronic bk.)
020 $z 9789813271876 $q (pbk.)
020 $z 9813271876 $q (pbk.)
020 $z 9789813271487 $q (hbk.)
020 $z 9813271485 $q (hbk.)
035 $a 00011021
040 $a WSPC $b eng $c WSPC
041 0 $a eng
050 0 4 $a QA279.5 $b .B39 2019
082 0 4 $a 519.542 $2 23
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 558567
650 0 $a Fault location (Engineering) $3 510431
650 0 $a Neural networks (Computer science) $3 386157
650 0 $a Electronic books. $2 local $3 376747
700 1 $a Cai, Baoping. $3 709924
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/11021#t=toc

based on 0 review(s)

Multimedia

Multimedia file
https://www.worldscientific.com/worldscibooks/10.1142/11021#t=toc

Reviews

Add a review and share your thoughts with other readers

Export

pickup library