Fuzzy Dynamic Adaptation of Parameters in the Water Cycle Algorithm
2017
This paper describes the enhancement of the water cycle algorithm (WCA) using a fuzzy inference system to dynamically adapt its parameters. The original WCA is compared in terms of performance with the proposed method called WCA with dynamic parameter adaptation (WCA-DPA). Simulation results on a set of well-known test functions show that the WCA is improved with a fuzzy dynamic adaptation of the parameters.
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