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

被引：0

作者：

Tan, Shing Chiang ^{[1
]}

Rao, M. V. C. ^{[1
]}

Lim, Chee Peng ^{[2
]}

机构：

[1] Multimedia Univ, Melaka, Malaysia

[2] Univ Sci Malaysia, Gelugor, Penang, Malaysia

来源：

2007 THIRD INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING, VOL 1, PROCEEDINGS | 2007年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 FAM-EP 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.

引用

页码：65 / +

页数：2

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