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We study the use of simulated annealing to optimize the membership functions of Takagi-Sugeno rules. The necessaryadaptation of simulated annealing in order to be efficient for this problem is discussed in detail. The convergence iscarefully studied for the test application of the approximation of an analytical function specially built to test the efficiencyof the algorithm. The obtained results...
We show that a genetic algorithm can tune the parameters of the membership functions and outputs of a Takagi-Sugeno fuzzy rule base. The method is systematically tested for the approximation of one-input analytical function.
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