Parametric Optimization of a Fuzzy Identification System, Using Distributed Genetic Algorithm with Dynamic Migration Period
نویسنده
چکیده
A type of distributed genetic algorithm (DGA), with dynamic determination of the migration period is proposed. The algorithm is especially well suited for the parametric optimization of fuzzy identification systems and its implementation on heterogeneous clusters. The results of the parametric optimization of a Takagi-Sugeno-Kang (TSK) identification system for a bio-technological (fermentative) process are shown, including the analysis of the solution’s quality, and the speedup obtained when nodes are added to the cluster.
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