Fuzzy C-means Based on Cooperative QPSO with Learning Behavior

被引:1
作者
Lu, Ping [1 ]
Dong, Husheng [1 ,2 ]
Zhai, Huanhuan [2 ]
Gong, Shengrong [2 ]
机构
[1] Suzhou Inst Trade & Commerce, Dept Informat, Suzhou, Peoples R China
[2] Soochow Univ, Sch Comp Sci & Technol, Suzhou, Peoples R China
来源
INTELLIGENCE SCIENCE AND BIG DATA ENGINEERING: BIG DATA AND MACHINE LEARNING TECHNIQUES, ISCIDE 2015, PT II | 2015年 / 9243卷
关键词
Fuzzy C-means; Clustering; Quantum-behaved particle swarm optimization; Cooperative evolution; Learning behavior;
D O I
10.1007/978-3-319-23862-3_34
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose an improved fuzzy C-means clustering algorithm based on cooperative quantum-behaved particle swarm optimization with learning behavior. Though FCM is a widely used clustering method, it has the inherent limitation of being sensitive to initial value and prone to fall in local optimum. To address this problem, we utilize the widely used global searching algorithm-QPSO, and employ new strategies to enhance its performance. First, we use the cooperative evolution strategy to improve the global searching capacity. Second, for each particle, the behavior of learning from others is granted, which effectively boosts the local searching capability. Furthermore, a gene pool is constructed to share information among all subgroups periodically. Since the iteration process is replaced by the improved version of QPSO, FCM no longer depends on the initialization values. Our experiments show that the proposed algorithm outperforms FCM and its improved versions significantly. The convergence and clustering accuracy are both improved effectively.
引用
收藏
页码:343 / 351
页数:9
相关论文
共 14 条
  • [1] [Anonymous], 2013, J COMPUT SIMUL
  • [2] [Anonymous], 2012, J COMPUT ENG APPL
  • [3] Chen X., 2012, J COMPUTER RES DEV S, P287
  • [4] Di Zhou, 2010, 2010 Third International Workshop on Advanced Computational Intelligence (IWACI 2010), P344, DOI 10.1109/IWACI.2010.5585123
  • [5] Izakian H, 2009, WOR CONG NAT BIOL, P1689
  • [6] Data clustering: 50 years beyond K-means
    Jain, Anil K.
    [J]. PATTERN RECOGNITION LETTERS, 2010, 31 (08) : 651 - 666
  • [7] A novel chaotic particle swarm optimization based fuzzy clustering algorithm
    Li, Chaoshun
    Zhou, Jianzhong
    Kou, Pangao
    Xiao, Jian
    [J]. NEUROCOMPUTING, 2012, 83 : 98 - 109
  • [8] Li Y., 2012, NEUROCOMPUTING, V48, P173
  • [9] Long H., 2006, J APPL RES COMPUT, P45
  • [10] [龙海侠 LONG Haixia], 2006, [计算机应用研究, Application Research of Computers], V23, P40