Please use this identifier to cite or link to this item: https://doi.org/10.1007/BF00199472
Title: Clustering in non-stationary environments using a clan-based evolutionary approach
Authors: Babu, G.P. 
Issue Date: Sep-1995
Source: Babu, G.P. (1995-09). Clustering in non-stationary environments using a clan-based evolutionary approach. Biological Cybernetics 73 (4) : 367-374. ScholarBank@NUS Repository. https://doi.org/10.1007/BF00199472
Abstract: Clustering techniques are used to discover structure in data by optimizing a denned criterion function. Most of these methods assume that the data are stationary, and these techniques are based on gradient descent which converge to a locally optimal clustering. There are many potential applications that require clustering to be performed in non-stationary temporal environments. In this paper, we investigate the applicability of a clan-based evolutionary optimization method for clustering data in non-stationary environments. Due to the stochastic nature of the technique, the problem of becoming entrapped in local optima is avoided, and the method can converge to (nearly) optimal clusters. Different cases are considered in the experiments, and the results demonstrate the efficacy of the evolutionary approach for clustering time-varying data. © 1995 Springer-Verlag.
Source Title: Biological Cybernetics
URI: http://scholarbank.nus.edu.sg/handle/10635/116264
ISSN: 03401200
DOI: 10.1007/BF00199472
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