Rule pruning in a fuzzy rule-based classification system

Quteishat, Anas M. and Lim, Chee Peng 2006, Rule pruning in a fuzzy rule-based classification system, in AISM 2006 : Proceedings of the Second Asia International Symposium on Mechatronics 2006, [The Conference], [Hong Kong], pp. 1-1.


Title Rule pruning in a fuzzy rule-based classification system
Author(s) Quteishat, Anas M.
Lim, Chee Peng
Conference name Asia International Symposium on Mechatronics. (2006 : Hong Kong)
Conference location Hong Kong
Conference dates 12-15 Dec. 2006
Title of proceedings AISM 2006 : Proceedings of the Second Asia International Symposium on Mechatronics 2006
Editor(s) [Unknown]
Publication date 2006
Conference series Asia International Symposium on Mechatronics
Start page 1
End page 1
Total pages 1
Publisher [The Conference]
Place of publication [Hong Kong]
Summary In this paper, we purpose a rule pruning strategy to reduce the number of rules in a fuzzy rule-based classification system.A confidence factor, which is formulated based on the compatibility of the rules with the input patterns is under deployed for rule pruning.The pruning strategy aims at reducing the complexity of the fuzzy classification system and, at the same time, maintaining the accuracy rate at a good level.To evaluate the effectiveness of the pruning strategy, two benchmark data sets are first tested. Then, a fault classification problem with real senor measurements collected from a power generation plant is evaluated.The results obtained are analyzed and explained, and implications of the proposed rule pruning strategy to the fuzzy classification system are discussed.
Language eng
Field of Research 109999 Technology not elsewhere classified
Socio Economic Objective 970110 Expanding Knowledge in Technology
HERDC Research category EN.1 Other conference paper
Persistent URL http://hdl.handle.net/10536/DRO/DU:30050171

Document type: Conference Paper
Collection: Institute for Frontier Materials
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