Simple Search:

Fuzzy Rules Optimization in Fuzzy Expert System for Machinability Data Selection: Genetic Algorithms Approach


Citation

Wong, Shaw Voon and Salem Hamouda, Abdel Magid (2001) Fuzzy Rules Optimization in Fuzzy Expert System for Machinability Data Selection: Genetic Algorithms Approach. Pertanika Journal of Science & Technology, 9 (2). pp. 209-218. ISSN 0128-7680

Abstract / Synopsis

Machinability data selection is complex and cannot be easily formulated by any mathematical model to meet design specification. Fuzzy logic is a good approach to solve such problems. Fuzzy rules optimization is always a problems for a complex fuzzy rules from more than 10 thousand combinations. (Wong et aL 1997) developed fuzzy models for machinability data selection. There are more than 2 x 1029 possible sets of rules for each model. Situation would be more complicated if further increase the number of inputs and/or outputs. The fuzzy rules were selected by trial and error and intuition in reference (Wong et aL 1997). Genetic optimization is suggested in this paper to further optimizing the fuzzy rules optimization with genetic algorithms has been developed. Weighted centroid method is used for output defuzzi fication to save processing time. Comparisons between the results of the new models and the previously published literatures are made.


Download File

[img]
Preview
PDF
Fuzzy_Rules_Optimization_in_Fuzzy_Expert_System_for.pdf

Download (2MB)

Additional Metadata

Item Type: Article
Publisher: Universiti Putra Malaysia Press
Keywords: Fuzzy rules optimization, genetic algorithm, fuzzy expert system, machinability data
Depositing User: Nur Izzati Mohd Zaki
Date Deposited: 30 Nov 2009 16:54
Last Modified: 27 May 2013 15:10
URI: http://psasir.upm.edu.my/id/eprint/3643
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item