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An Efficient Cuckoo Search Algorithm for System-Level Fault Diagnosis

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We propose a new efficient algorithm named Cuckoo search fault diagnosis (CSFD) to solve system-level fault diagnosis problem.KMP algorithm is proposed for initialization based on the K-means partition algorithm;a fitness function is designed according to the equation constraints satisfied by the test model;the binary mapping method is advanced by optimizing existing binary mapping algorithm.Experiments show that KMP algorithm significantly reduces the disparity between the initial solution and the actual solution,and CSFD algorithm improves the efficiency and correctness significantly compared with existing typical swarm intelligence diagnosis algorithm.

System-level fault diagnosisEquation modelCuckoo searchK-means clusteringCuckoo search fault diagnosis algorithm (CSFD)

XUAN Hengnong、ZHANG Runchi、SHI Shengsheng

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School of Information Engineering, Nanjing University of Finance and Economics, Nanjing 210046, China

Department of Computer Science and Technology, Nanjing University, Nanjing 210023, China

This work is supported by the National Natural Science Foundation of ChinaThis work is supported by the National Natural Science Foundation of China

9071800861133015

2016

10.1049/cje.2016.06.035

电子学报(英文)

电子学报(英文)

CSTPCDSCIEI
ISSN：1022-4653
年,卷(期)：2016.25(6)
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