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The Scientific World Journal
Volume 2015 (2015), Article ID 929471, 8 pages
Research Article

A Novel Clustering Algorithm Inspired by Membrane Computing

1Center for Radio Administration and Technology Development, Xihua University, Chengdu 610039, China
2School of Mathematics and Computer Engineering, Xihua University, Chengdu 610039, China
3School of Electrical and Information Engineering, Xihua University, Chengdu 610039, China

Received 10 June 2014; Accepted 7 September 2014

Academic Editor: Shifei Ding

Copyright © 2015 Hong Peng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


P systems are a class of distributed parallel computing models; this paper presents a novel clustering algorithm, which is inspired from mechanism of a tissue-like P system with a loop structure of cells, called membrane clustering algorithm. The objects of the cells express the candidate centers of clusters and are evolved by the evolution rules. Based on the loop membrane structure, the communication rules realize a local neighborhood topology, which helps the coevolution of the objects and improves the diversity of objects in the system. The tissue-like P system can effectively search for the optimal partitioning with the help of its parallel computing advantage. The proposed clustering algorithm is evaluated on four artificial data sets and six real-life data sets. Experimental results show that the proposed clustering algorithm is superior or competitive to k-means algorithm and several evolutionary clustering algorithms recently reported in the literature.