Membrane Clustering: A Novel Clustering Algorithm under Membrane Computing
Year: 2014
Type: conference-paper
Abstract: Membrane computing (known as P systems) is a class of distributed parallel \ncomputing models, this paper presents a novel algorithm under membrane computing \nfor solving the data clustering problem, called as membrane clustering algorithm. The \nclustering algorithm is based on a tissue-like P system with a loop structure of cells. \nThe objects of the cells express the candidate cluster centers and are evolved by the \nevolution rules. Based on the loop membrane structure, the communication rules realize \na local neighborhood topology, which helps the co-evolution of the objects and improves \nthe diversity of objects in the system. The tissue-like P system can effectively search \nfor the optimal clustering partition with the help of its parallel computing advantage. \nThe proposed clustering algorithm is evaluated on four artificial data sets and six real-life \ndata sets. Experimental results show that the proposed clustering algorithm is superior or \ncompetitive to classical k-means algorithm and several evolutionary clustering algorithms \nrecently reported in the literature.
Authors: Hong Peng, Jiarong Zhang, Jun Wang, Tao Wang, Mario J. Pérez–Jiménez, Agustín Riscos–Núñez
Language: English
Topic: DNA and Biological Computing
Subfield: Theoretical Computer Science
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2273579293