[1]ZHANG Yongku,YIN Lingxue,SUN Jinguang.Fuzzy clustering algorithm based on the improved genetic algorithm[J].CAAI Transactions on Intelligent Systems,2015,10(4):627-635.[doi:10.3969/j.issn.1673-4785.201503033]
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Fuzzy clustering algorithm based on the improved genetic algorithm

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 10 Number of periods: 2015 4 Page number: 627-635 Column: 学术论文—机器学习 Public date: 2015-08-25
Title:
Fuzzy clustering algorithm based on the improved genetic algorithm
Author(s):
ZHANG Yongku1;  YIN Lingxue2;  SUN Jinguang1
1. College of Electronics and Information Engineering, Liaoning Technical University, Liaoning 125105, China;
2. Institute of Graduate, Liaoning Technical University, Liaoning 125105, China
Keywords:
fuzzy C-means clustering; cluster analysis; genetic algorithm; dynamic analysis; fuzzy clustering; initial values; premature contraction avoidance; global optimum; local optimum
CLC:
TP18
DOI:
10.3969/j.issn.1673-4785.201503033
Abstract:
The traditional fuzzy C-means(FCM) clustering algorithm is prone to fall into the solution of local optimum and is sensitive to initial value. Aiming at these drawbacks, a fuzzy C-means based on the improved genetic algorithm is presented. The improved genetic algorithm is employed to optimise the FCM algorithm, finding the cluster center of the global optimum. Finally, the experimental results show that compared with the traditional FCM, the proposed algorithm has stronger optimisation ability and better clustering effect.
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