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Fuzzy rule base learning through simulated annealing

✍ Scribed by Francois Guély; Rémy La; Patrick Siarry

Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
764 KB
Volume
105
Category
Article
ISSN
0165-0114

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✦ Synopsis

We study the use of simulated annealing to optimize the membership functions of Takagi-Sugeno rules. The necessary adaptation of simulated annealing in order to be efficient for this problem is discussed in detail. The convergence is carefully studied for the test application of the approximation of an analytical function specially built to test the efficiency of the algorithm. The obtained results are compared with gradient descent optimization results. We point out that simulated annealing is particularly interesting in the case (usual in practical implementations) when there are few rules compared to the complexity of the problem.

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