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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
computer science
Memetic multiobjective particle swarm optimization-based radial basis function network for classification problems
Information Sciences, Volume 239, Year 2013
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Description
This paper presents a new multiobjective evolutionary algorithm applied to a radial basis function (RBF) network design based on multiobjective particle swarm optimization augmented with local search features. The algorithm is named the memetic multiobjective particle swarm optimization RBF network (MPSON) because it integrates the accuracy and structure of an RBF network. The proposed algorithm is implemented on two-class and multiclass pattern classification problems with one complex real problem. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multiobjective RBF networks with good generalization capability and compact network structure. The accuracy and complexity of the network obtained by the proposed algorithm are compared with the memetic non-dominated sorting genetic algorithm based RBF network (MGAN) through statistical tests. This study shows that MPSON generates RBF networks coming with an appropriate balance between accuracy and simplicity, outperforming the other algorithms considered. © 2013 Elsevier Inc. All rights reserved.
Authors & Co-Authors
Qasem, Sultan Noman
Saudi Arabia, Riyadh
Al-imam Muhammad Ibn Saud Islamic University
Yemen, Taiz
Taiz University
Shamsuddin, Šiti Mariyam Hj
Malaysia, Johor Bahru
Universiti Teknologi Malaysia
Hashim, Siti Zaiton Mohd
Malaysia, Johor Bahru
Universiti Teknologi Malaysia
Darus, M.
Malaysia, Bangi
Universiti Kebangsaan Malaysia
Al-Shammari, Eiman Tamah
Kuwait, Kuwait City
Kuwait University
Statistics
Citations: 65
Authors: 5
Affiliations: 5
Identifiers
Doi:
10.1016/j.ins.2013.03.021
ISSN:
00200255
Research Areas
Genetics And Genomics