Integrating nature-inspired optimization algorithms to K-means clustering
作者： Rui Tang , Simon Fong , Xin-She Yang , Suash Deb
DOI: 10.1109/ICDIM.2012.6360145
关键词: CURE data clustering algorithm 、 Cluster analysis 、 Constrained clustering 、 Biclustering 、 Artificial intelligence 、 Correlation clustering 、 Canopy clustering algorithm 、 Mathematical optimization 、 Multi-swarm optimization 、 Metaheuristic 、 Computer science
摘要: Although K-means clustering algorithm is simple and popular, it has a fundamental drawback of falling into local optima that depend on the randomly generated initial centroid values. Optimization algorithms are well known for their ability to guide iterative computation in searching global optima. They also speed up process by achieving early convergence. Contemporary optimization inspired biology, including Wolf, Firefly, Cuckoo, Bat Ant algorithms, simulate swarm behavior which peers attracted while steering towards objective. It found these bio-inspired have own virtues could be logically integrated avoid during iteration In this paper, constructs integration methods presented. The extended versions with produce improved results. Experiments conducted validate benefits proposed approach.
umac.mo
sci-hub.se 参考文章(11)
Xin-She Yang, Firefly algorithms for multimodal optimization international conference on stochastic algorithms foundations and applications. pp. 169- 178 ,(2009) , 10.1007/978-3-642-04944-6_14
Xin-She Yang, Suash Deb, Simon Fong, Accelerated Particle Swarm Optimization and Support Vector Machine for Business Optimization and Applications networked digital technologies. pp. 53- 66 ,(2011) , 10.1007/978-3-642-22185-9_6
Rui Tang, Simon Fong, Xin-She Yang, Suash Deb, Wolf search algorithm with ephemeral memory international conference on digital information management. pp. 165- 172 ,(2012) , 10.1109/ICDIM.2012.6360147
Xin-She Yang, Suash Deb, Cuckoo Search via Lévy flights nature and biologically inspired computing. pp. 210- 214 ,(2009) , 10.1109/NABIC.2009.5393690
J. Senthilnath, S.N. Omkar, V. Mani, Clustering using firefly algorithm: Performance study Swarm and evolutionary computation. ,vol. 1, pp. 164- 171 ,(2011) , 10.1016/J.SWEVO.2011.06.003
Shokri Z. Selim, M. A. Ismail, K-Means-Type Algorithms: A Generalized Convergence Theorem and Characterization of Local Optimality IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. PAMI-6, pp. 81- 87 ,(1984) , 10.1109/TPAMI.1984.4767478
Benoit B. Mandelbrot, The Fractal Geometry of Nature ,(1982)
M. Dorigo, V. Maniezzo, A. Colorni, Ant system: optimization by a colony of cooperating agents systems man and cybernetics. ,vol. 26, pp. 29- 41 ,(1996) , 10.1109/3477.484436
J. B. Macqueen, Some methods for classification and analysis of multivariate observations Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Volume 1: Statistics. ,vol. 1, pp. 281- 297 ,(1967)
D Karaboga, AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION TECHNICAL REPORT. pp. 0- 0 ,(2005)