Abstract
The proposal described in this paper uses the Differential Evolution (DE) algorithm as an optimization method in which we want to dynamically adapt its parameters using fuzzy logic control systems, with the goal that the fuzzy system calculates the optimal parameter values of the DE algorithm to find better results, depending on the type of problems the DE is applied. In this case we consider a fuzzy system to dynamically change the F and CR variables.
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Ochoa, P., Castillo, O., Soria, J. (2015). Differential Evolution with Dynamic Adaptation of Parameters for the Optimization of Fuzzy Controllers. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization. Studies in Computational Intelligence, vol 601. Springer, Cham. https://doi.org/10.1007/978-3-319-17747-2_44
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DOI: https://doi.org/10.1007/978-3-319-17747-2_44
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