Conference paper
Predefining Numbers of Fuzzy Sets for Genetically Generated Fuzzy Knowledge Bases Using Clustering Techniques: Application to Tool Wear Monitoring
Department of Mechanical Engineering, École Polytechnique de Montréal, C.P. 6079, Succ. Centre-Ville, Montréal, H3C 3A7, Canada, sofiane.achiche@polymtl.ca1
Department of Mechanical Engineering, École Polytechnique de Montréal, C.P. 6079, Succ. Centre-Ville, Montréal, H3C 3A7, Canada, marek.balazinski@polymtl.ca2
Department of Mechanical Engineering, École Polytechnique de Montréal, C.P. 6079, Succ. Centre-Ville, Montréal, H3C 3A7, Canada, aleksander.przybylo@polymtl.ca3
Department of Mechanical Engineering, École Polytechnique de Montréal, C.P. 6079, Succ. Centre-Ville, Montréal, H3C 3A7, Canada, luc.baron@polymtl.ca4
One of the problems surrounding fuzzy knowledge base generation using genetic algorithms is finding an optimal number of fuzzy sets for each premise. A Genetic algorithm developed by the authors for the automatic generation of fuzzy knowledge bases uses a multi-objective method combining error minimization and simplification.
This paper proposes solutions based on cluster analysis and validation indices for the numbers of clusters used in predefining the numbers of fuzzy sets. Two different validation indices as well as a combination of one of these with the multi-objective method are compared to the original multi-objective method on both synthetic and experimental data.
Results obtained with the proposed techniques showed a considerable improvement over the multi-objective method on both data sets.
| Language: | English |
|---|---|
| Year: | 2006 |
| Pages: | 35-40 |
| ISBN: | 1424403626 , 1424403634 , 9781424403622 and 9781424403639 |
| Types: | Conference paper |
| DOI: | 10.1109/NAFIPS.2006.365855 |
Clustering algorithms Evolutionary computation Fuzzy sets Genetic algorithms Genetic engineering Knowledge engineering Minimization methods Monitoring Shape Stochastic processes clustering techniques computerised monitoring condition monitoring fuzzy knowledge base generation fuzzy set theory fuzzy sets genetic algorithms knowledge based systems machine tools mechanical engineering computing multi-objective method pattern clustering tool wear monitoring validation indices wear
