Research on fault diagnosis technology of heat meter based on multi classifier fusion of pigeon swarm algorithm

In order to improve the availability of fault data, the fault data of heat meters had been classified, and balances all kinds of fault data according to interpolation algorithms to meet the needs of fault diagnosis algorithms. Based on the voting mechanism, an integrated model of multi classifier fu...

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Vydáno v:Mathematical biosciences and engineering : MBE Ročník 20; číslo 4; s. 6312 - 6326
Hlavní autoři: Yu, Shuchun, Tao, Jinjian, Liu, Jun, Miao, Yanshu
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States AIMS Press 01.01.2023
Témata:
fault diagnosis
heat meter
integrated model
pigeon swarm algorithm
fault diagnosis
pigeon swarm algorithm
integrated model
heat meter
ISSN:1551-0018, 1551-0018
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Shrnutí:In order to improve the availability of fault data, the fault data of heat meters had been classified, and balances all kinds of fault data according to interpolation algorithms to meet the needs of fault diagnosis algorithms. Based on the voting mechanism, an integrated model of multi classifier fusion is established, and the weight of each classifier is optimally configured through pigeon swarm algorithm. In the experiment, three kinds of integration models are obtained according to the voting mechanism and pigeon swarm algorithm. The three integrated models are used to diagnose the fault of the heat meter, and the three indicators of precision, recall and F1 Core have achieved satisfactory results.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 23
ISSN:1551-0018
1551-0018
DOI:10.3934/mbe.2023272