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An improved FCM algorithm with adaptive weights based on SA-PSO
Wu, Ziheng1,2; Wu, Zhongcheng1; Zhang, Jun1
2017-10-01
发表期刊NEURAL COMPUTING & APPLICATIONS
卷号28期号:10页码:3113-3118
摘要Fuzzy c-means clustering algorithm (FCM) often used in pattern recognition is an important method that has been successfully used in large amounts of practical applications. The FCM algorithm assumes that the significance of each data point is equal, which is obviously inappropriate from the viewpoint of adaptively adjusting the importance of each data point. In this paper, considering the different importance of each data point, a new clustering algorithm based on FCM is proposed, in which an adaptive weight vector W and an adaptive exponent p are introduced and the optimal values of the fuzziness parameter m and adaptive exponent p are determined by SA-PSO when the objective function reaches its minimum value. In this method, the particle swarm optimization (PSO) is integrated with simulated annealing (SA), which can improve the global search ability of PSO. Experimental results have demonstrated that the proposed algorithm can avoid local optima and significantly improve the clustering performance.
文章类型Article
关键词Fuzzy C-means Clustering Algorithm Particle Swarm Optimization Simulated Annealing Adaptive Weight
WOS标题词Science & Technology ; Technology
DOI10.1007/s00521-016-2786-6
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000411176800021
引用统计
文献类型期刊论文
条目标识符http://ir.hfcas.ac.cn:8080/handle/334002/33665
专题中科院强磁场科学中心
作者单位1.Chinese Acad Sci, High Field Magnet Lab, Hefei, Anhui, Peoples R China
2.Univ Sci & Technol China, Hefei, Anhui, Peoples R China
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Wu, Ziheng,Wu, Zhongcheng,Zhang, Jun. An improved FCM algorithm with adaptive weights based on SA-PSO[J]. NEURAL COMPUTING & APPLICATIONS,2017,28(10):3113-3118.
APA Wu, Ziheng,Wu, Zhongcheng,&Zhang, Jun.(2017).An improved FCM algorithm with adaptive weights based on SA-PSO.NEURAL COMPUTING & APPLICATIONS,28(10),3113-3118.
MLA Wu, Ziheng,et al."An improved FCM algorithm with adaptive weights based on SA-PSO".NEURAL COMPUTING & APPLICATIONS 28.10(2017):3113-3118.
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