An Extended Membrane System with Active Membranes to Solve Automatic Fuzzy Clustering Problems

International Journal of Neural Systems
Hong PengAgustín Riscos-Núñez

Abstract

This paper focuses on automatic fuzzy clustering problem and proposes a novel automatic fuzzy clustering method that employs an extended membrane system with active membranes that has been designed as its computing framework. The extended membrane system has a dynamic membrane structure; since membranes can evolve, it is particularly suitable for processing the automatic fuzzy clustering problem. A modification of a differential evolution (DE) mechanism was developed as evolution rules for objects according to membrane structure and object communication mechanisms. Under the control of both the object's evolution-communication mechanism and the membrane evolution mechanism, the extended membrane system can effectively determine the most appropriate number of clusters as well as the corresponding optimal cluster centers. The proposed method was evaluated over 13 benchmark problems and was compared with four state-of-the-art automatic clustering methods, two recently developed clustering methods and six classification techniques. The comparison results demonstrate the superiority of the proposed method in terms of effectiveness and robustness.

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Citations

Sep 29, 2018·Reviews in the Neurosciences·Golrokh Mirzaei, Hojjat Adeli
Oct 7, 2017·International Journal of Neural Systems·Linqiang PanFerrante Neri
May 30, 2020·International Journal of Neural Systems·Saeed Reza Kheradpisheh, Timothée Masquelier
Mar 15, 2020·International Journal of Neural Systems·Hong PengAgustín Riscos-Núñez
Aug 25, 2020·Computational Intelligence and Neuroscience·Xiyu LiuNing Wang
Nov 10, 2020·International Journal of Neural Systems·Tingfang WuLinqiang Pan
Jul 27, 2021·Computational and Mathematical Methods in Medicine·Haris MasoodSeifedine Kadry

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