Fuzzy ARTMAP and hybrid evolutionary programming for pattern classification

Tan, Shing Chiang and Lim, Chee Peng 2011, Fuzzy ARTMAP and hybrid evolutionary programming for pattern classification, Journal of intelligent and fuzzy systems, vol. 22, no. 2-3, pp. 57-68.

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Title Fuzzy ARTMAP and hybrid evolutionary programming for pattern classification
Author(s) Tan, Shing Chiang
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Journal name Journal of intelligent and fuzzy systems
Volume number 22
Issue number 2-3
Start page 57
End page 68
Total pages 12
Publisher IOS Press
Place of publication Amsterdam, The Netherlands
Publication date 2011
ISSN 1064-1246
Keyword(s) fuzzy ARTMAP
hybrid evolutionary programming
medical diagnosis
pattern classification
Summary In this paper, an Evolutionary Artificial Neural Network (EANN) that combines the Fuzzy ARTMAP (FAM) network and a Hybrid Evolutionary Programming (HEP) model is introduced. The proposed FAM-HEP model, which combines the strengths of FAM and HEP, is able to construct its network structure autonomously as well as to perform learning and evolutionary search and adaptation concurrently. The effectiveness of the proposed FAM-HEP network is assessed empirically using several benchmark data sets and a real medical diagnosis problem. The performance of FAM-HEP is analyzed, and the results are compared with those of FAM-EP, FAM, and other classification models. In general, the results of FAM-HEP are better than those of FAM-EP and FAM, and are comparable with those from other classification models. The study also reveals the potential of FAM-HEP as an innovative EANN model for undertaking pattern classification problems in general, and a promising computerized decision support tool for tackling medical diagnosis tasks in particular.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2011, IOS Press and the authors. All rights reserved
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048754

Document type: Journal Article
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