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

Tan, Shing Chiang, Rao, M. V. C. and Lim, Chee Peng 2007, A mutation-based evolving neural network model and its application to condition monitoring, in IIHMSP 2007 : Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IEEE, Los Alamitos, Calif., pp. 65-68.

Attached Files
Name Description MIMEType Size Downloads

Title A mutation-based evolving neural network model and its application to condition monitoring
Author(s) Tan, Shing Chiang
Rao, M. V. C.
Lim, Chee Peng
Conference name Intelligent Information Hiding and Multimedia Signal Processing. Conference (3rd : 2007 : Kaohsiung, Taiwan)
Conference location Kaohsiung, Taiwan
Conference dates 26-28 Nov. 2007
Title of proceedings IIHMSP 2007 : Proceedings of the 3rd International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Editor(s) [unknown]
Publication date 2007
Conference series Intelligent Information Hiding and Multimedia Signal Processing. Conference
Start page 65
End page 68
Total pages 4
Publisher IEEE
Place of publication Los Alamitos, Calif.
Keyword(s) neural network
condition monitoring
Summary 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.
Language eng
Field of Research 099999 Engineering not elsewhere classified
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2007, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048104

Document type: Conference Paper
Collection: Institute for Frontier Materials
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Versions
Version Filter Type
Access Statistics: 38 Abstract Views, 7 File Downloads  -  Detailed Statistics
Created: Mon, 03 Sep 2012, 15:32:49 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.