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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
Source PublicationNEURAL COMPUTING & APPLICATIONS
Volume28Issue:10Pages:3113-3118
AbstractFuzzy 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.
SubtypeArticle
KeywordFuzzy C-means Clustering Algorithm Particle Swarm Optimization Simulated Annealing Adaptive Weight
WOS HeadingsScience & Technology ; Technology
DOI10.1007/s00521-016-2786-6
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000411176800021
Citation statistics
Document Type期刊论文
Identifierhttp://ir.hfcas.ac.cn:8080/handle/334002/33665
Collection中科院强磁场科学中心
Affiliation1.Chinese Acad Sci, High Field Magnet Lab, Hefei, Anhui, Peoples R China
2.Univ Sci & Technol China, Hefei, Anhui, Peoples R China
Recommended Citation
GB/T 7714
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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