An online pruning strategy for supervised ARTMAP-based neural networks

Tan, Shing Chiang, Rao, M. V. C. and Lim, Chee Peng 2009, An online pruning strategy for supervised ARTMAP-based neural networks, Neural computing and applications, vol. 18, no. 4, pp. 387-395.

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Title An online pruning strategy for supervised ARTMAP-based neural networks
Author(s) Tan, Shing Chiang
Rao, M. V. C.
Lim, Chee PengORCID iD for Lim, Chee Peng
Journal name Neural computing and applications
Volume number 18
Issue number 4
Start page 387
End page 395
Total pages 9
Publisher Springer UK
Place of publication London, England
Publication date 2009-05
ISSN 0941-0643
Keyword(s) dynamic decay adjustment
fuzzy ARTMAP
online pruning
Summary Identifying an appropriate architecture of an artificial neural network (ANN) for a given task is important because learning and generalisation of an ANN is affected by its structure. In this paper, an online pruning strategy is proposed to participate in the learning process of two constructive networks, i.e. fuzzy ARTMAP (FAM) and fuzzy ARTMAP with dynamic decay adjustment (FAMDDA), and the resulting hybrid networks are called FAM/FAMDDA with temporary nodes (i.e. FAM-T and FAMDDA-T, respectively). FAM-T and FAMDDA-T possess a capability of reducing the network complexity online by removing unrepresentative neurons. The performances of FAM-T and FAMDDA-T are evaluated and compared with those of FAM and FAMDDA using a total of 13 benchmark data sets. To demonstrate the applicability of FAM-T and FAMDDA-T, a real fault detection and diagnosis task in a power plant is tested. The results from both benchmark studies and real-world application show that FAMDDA-T and FAM-T are able to yield satisfactory classification performances, with the advantage of having parsimonious network structures.
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
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Document type: Journal Article
Collection: Institute for Frontier Materials
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