An automatic clustering algorithm inspired by membrane computing

Abstract

Membrane computing is a class of distributed parallel computing models. Inspired from the structure and inherent mechanism of membrane computing, a membrane clustering algorithm is proposed to deal with automatic clustering problem, in which a tissue-like membrane system with fully connected structure is designed as its computing framework. Moreover, based on its special structure and inherent mechanism, an improved velocity-position model is developed as evolution rules. Under the control of evolution-communication mechanism, the tissue-like membrane system cannot only find the most appropriate number of clusters but else determine a good clustering partitioning for a data set. Six benchmark data sets are used to evaluate the proposed membrane clustering algorithm. Experiment results show that the proposed algorithm is superior or competitive to three state-and-the-art automatic clustering algorithms recently reported in the literature.