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A mutation-based evolving neural network model and its application to condition monitoring

conference contribution
posted on 2007-01-01, 00:00 authored by S Tan, M Rao, Chee Peng LimChee Peng Lim
Data analysis using intelligent systems is a key solution to many industrial problems. In this paper, a mutation-based evolving artificial neural network, which is based on an integration of the Fuzzy ARTMAP (FAM) neural network and evolutionary programming (EP), is proposed. The proposed FAMEP model is applied to detect and classify possible faults from a number of sensory signals of a circulating water system in a power generation plant. The efficiency of FAM-EP is assessed and compared with that of the original FAM network in terms of classification accuracy as well as network complexity. In addition, the bootstrap method is used to quantify the performance statistically. The results positively demonstrate the usefulness of FAM-EP in tackling data classification problems.

History

Event

Intelligent Information Hiding and Multimedia Signal Processing. Conference (3rd : 2007 : Kaohsiung, Taiwan)

Pagination

65 - 68

Publisher

IEEE

Location

Kaohsiung, Taiwan

Place of publication

Los Alamitos, Calif.

Start date

2007-11-26

End date

2007-11-28

Language

eng

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2007, IEEE

Title of proceedings

IIHMSP 2007 : Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing