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2007 International Conference on Computational Intelligence and Multimedia Applications
An Efficient Hybrid Algorithm for Data Clustering Using Improved Genetic Algorithm and Nelder Mead Simplex Search
Sivakasi, Tamil Nadu, India
December 13-December 15
ISBN: 0-7695-3050-8
Data clustering is a process of putting similar data into groups. A clustering algorithm partitions a data set into several groups such that the similarity within a group is larger than among groups. This paper presents data clustering using improved genetic algorithm (IGA) and the popular Nelder-Mead(NM) Simplex search . To improve the accuracy of data clustering, an improved GA (IGA) is used. The performance of IGA is established with many benchmark test functions optimization. To accelerate the clustering process further more a hybrid algorithm based on improved GA and Nelder-Mead simplex search(NM) is suggested for clustering and is tested on 7 datasets and its performance is compared with above two algorithms and the traditional K-means algorithm. Keywords--Clustering, Improved Genetic Algorithm, K-means, Nelder-Mead, Hybrid algorithm
Citation:
Suresh Chandra Satapathy, Jvr Murthy, P.V.G.D. Prasada Reddy, Venkatesh Katari, Satish Malireddi, V.N.K. Srujan Kollisetty, "An Efficient Hybrid Algorithm for Data Clustering Using Improved Genetic Algorithm and Nelder Mead Simplex Search," iccima, vol. 1, pp.498-510, 2007 International Conference on Computational Intelligence and Multimedia Applications, 2007
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