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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 LimData 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.
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Event
Intelligent Information Hiding and Multimedia Signal Processing. Conference (3rd : 2007 : Kaohsiung, Taiwan)Pagination
65 - 68Publisher
IEEELocation
Kaohsiung, TaiwanPlace of publication
Los Alamitos, Calif.Publisher DOI
Start date
2007-11-26End date
2007-11-28Language
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2007, IEEETitle of proceedings
IIHMSP 2007 : Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal ProcessingUsage metrics
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