Adaptive fuzzy clustering approach based on evolutionary cat swarm optimization

Abstract

Computational intelligence methods are widely used to solve many complex problems, including, of course, traditional: Data Mining and such new directions as Dynamic Data Mining, Data Stream Mining, Big Data Mining, Web Mining, Text Mining, etc. One of the main areas of computational intelligence are evolutionary algorithms that essentially represent certain mathematical models of biological organisms evolution. In the paper adaptive methods of fuzzy clustering using on evolutionary cat swarm optimization were proposed. Using proposed approach it's possible to solve clustering task in on-line mode.