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Article

Fault Classification Decision Fusion System Based on Combination Weights and an Improved Voting Method

by 1, 2,*, 2,* and 2
1
Institute of Information and Control, School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
2
School of Engineering, Huzhou University, Huzhou 313000, China
*
Authors to whom correspondence should be addressed.
Processes 2019, 7(11), 783; https://doi.org/10.3390/pr7110783
Received: 25 September 2019 / Revised: 19 October 2019 / Accepted: 25 October 2019 / Published: 1 November 2019
It is difficult to correctly classify all faults by using only one classifier, and the performance of most classifiers varies under different conditions. In view of this, a new decision fusion system is proposed to solve the problem of fault classification. The proposed decision fusion system is innovative in two aspects: the use of combined weights and a new improved voting method. The combined weights integrate the subjective and objective weights, where the analytic hierarchy process and entropy weight-technique for order performance by similarity to ideal solution are used to determine the subjective and objective weights of different base classifiers under multiple performance evaluation indicators. Moreover, a new improved voting method based on the concept of classifier validity is proposed to increase the accuracy of the decision system. Finally, the method is validated by the Tennessee Eastman benchmark process, and the classification accuracy of the new method is shown to be improved by more than 5.06% compared to the best base classifier. View Full-Text
Keywords: ensemble method; fault classification; analytic hierarchy process; entropy weight method; decision fusion ensemble method; fault classification; analytic hierarchy process; entropy weight method; decision fusion
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MDPI and ACS Style

Zeng, F.; Li, Z.; Zhou, Z.; Du, S. Fault Classification Decision Fusion System Based on Combination Weights and an Improved Voting Method. Processes 2019, 7, 783. https://doi.org/10.3390/pr7110783

AMA Style

Zeng F, Li Z, Zhou Z, Du S. Fault Classification Decision Fusion System Based on Combination Weights and an Improved Voting Method. Processes. 2019; 7(11):783. https://doi.org/10.3390/pr7110783

Chicago/Turabian Style

Zeng, Fanliang, Zuxin Li, Zhe Zhou, and Shuxin Du. 2019. "Fault Classification Decision Fusion System Based on Combination Weights and an Improved Voting Method" Processes 7, no. 11: 783. https://doi.org/10.3390/pr7110783

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