Integration of artificial immune network and K-means for cluster analysis

被引：0
作者：
R. J. Kuo
S. S. Chen
W. C. Cheng
C. Y. Tsai
机构：
[1] National Taiwan University of Science and Technology,Department of Industrial Management
[2] TSMC Solid State Lighting Co.,Department of Industrial Engineering and Management
[3] Ltd.,undefined
[4] Yuan Ze University,undefined
来源：
Knowledge and Information Systems | 2014年 / 40卷
关键词：
Cluster analysis; Artificial immune network; Artificial immune system; Particle swarm optimization algorithm ; K-means algorithm;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This study is dedicated to propose a cluster analysis algorithm which is integration of artificial immune network (aiNet) and K-means algorithm (aiNetK). Four benchmark data sets, Iris, Wine, Glass, and Breast Cancer, are employed to testify the proposed algorithm. The computational results reveal that aiNetK is superior to particle swam optimization and artificial immune system-related methods.
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页码：541 / 557
页数：16
相关论文
共 64 条
[1]  
Al-Sultan K(1995)A tabu search approach to the clustering problem Pattern Recognit 28 1443-1451
[2]  
Bezdek J(1980)A convergence theorem for the fuzzy ISO-DATA clustering algorithm IEEE Trans Pattern Anal Mach Intell 2 1-8
[3]  
Bezdek J(1992)Numerical convergence and interpretation of the fuzzy c-shells clustering algorithms IEEE Trans Neural Netw 3 787-793
[4]  
Hathaway R(2009)Applying artificial immune system and ant algorithm in air-conditioner market segmentation Expert Syst Appl 36 4437-4442
[5]  
Chiu CY(1965)Clustering analysis of multivariate data: efficiency versus interpretability of classification Biometrics 21 768-769
[6]  
Kuo IT(1999)Hierarchical unsupervised fuzzy clustering IEEE Trans Fuzzy Syst 7 723-733
[7]  
Lin CH(2000)ROCK: a robust clustering algorithm for categorical attributes Inf Syst 25 345-366
[8]  
Forgy E(1999)Clustering with a genetically optimized approach IEEE Trans Evol Comput 3 103-112
[9]  
Geva AB(2003)Exploiting the analogy between the immune system and sparse distributed memories Genet Program Evol Mach 4 333-358
[10]  
Guha S(1999)Chameleon: hierarchical clustering using dynamic modeling IEEE Comput 32 68-75
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