Abstract
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.
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