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This paper studies the use of Genetic Algorithms (GA) in the design of Fuzzy Logic Controllers (FLC) and show how population size, probability of crossover and rate of mutation can effect the performance of the GA. The comparison of various parameters shows that GA is helpful in improving the performance of FLC. A fuzzy logic is fully defined by its membership function. What is the best to determine...
This study investigates the use of Genetic Algorithms (GA) to the design and implementation of Fuzzy Logic Controllers (FLC). A fuzzy logic is fully defined by its membership function. What is the best to determine the membership function is the first question that has been tackled. Thus it is important to select the accurate membership functions but these methods possess one common weakness where...
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