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Caiping Hou
Shandong Normal University

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Tissue-like P system based DNA-GA for clustering Caiping Hou; Xiyu Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2015
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp565-573

Abstract

In recent years, DNA GA algorithm is drawing attention from scholars. The algorithm combines the DNA encoding and Genetic Algorithm, which solve the premature convergence of genetic algorithms, the weak local search capability and binary Hamming cliff problems effectively.How to design a more effective way to improve the performance of DNA-GA algorithm is more worth studying. As is known to all,the tissue-like P system can search for the optimal clustering partition with the help of its parallel computing advantage effectivel. This paper is under this premise and presents DNA-GA algorithm based on tissue-like P systems (TPDNA-GA) with a loop structure of cells, which aims to combine the parallelism and the evolutionary rules of tissue-like P systems to improve performance of the DNA-GA algorithm. The objective of this paper is to use the TPDNA-GA algorithm to support clustering in order to find the best clustering center.This algorithm is of particular interest to when dealing with large and heterogeneous data sets and when being faced with an unknown number of clusters. Experimental results show that the proposed TPDNA-GA algorithm for clustering is superior or competitive to classical k-means algorithm and several evolutionary clustering algorithms.
A New P System Based Genetic Algorithm Caiping Hou; Xiyu Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 1: October 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i1.pp165-168

Abstract

For the “early convergence” or the “genetic drift” of the genetic algorithm, this paper proposes a new genetic algorithm based on P system. Based on the parallel mechanism of P system in membrane computing, we put forward the new P system based genetic algorithm (PBGA). So that we can improve the performance of GA.
Co-Authors Xiyu Liu