Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/107130
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Type: Journal article
Title: An extended membrane system with active membranes to solve automatic fuzzy clustering problems
Author: Peng, H.
Wang, J.
Shi, P.
Pérez-Jiménez, M.
Riscos-Núñez, A.
Citation: International Journal of Neural Systems, 2016; 26(3):1650004-1-1650004-17
Publisher: World Scientific Publishing
Issue Date: 2016
ISSN: 0129-0657
1793-6462
Statement of
Responsibility: 
Hong Peng, Jun Wang, Peng Shi, Mario J. Pérez-Jiménez, Agustín 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.
Keywords: Data clustering; automatic fuzzy clustering problem; membrane computing; membrane systems with active membranes
Rights: © World Scientific Publishing Company
RMID: 0030042618
DOI: 10.1142/S0129065716500040
Appears in Collections:Electrical and Electronic Engineering publications

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