Self-organizing potential field network: a new optimization algorithm
IEEE Transactions on Neural Networks
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This work deals with an evolutionary data processing, concretely optimization of control of chaos based on using EA. The main aim of this work is to show that evolutionary algorithms are capable of optimization of chaos control. As models of deterministic chaotic system one dimensional Logistic equation and two dimensional Henon map were used. The evolutionary algorithm Self-Organizing Migrating Algorithm (SOMA) was used in four versions. For each version, simulations were repeated several times to show and check robustness of used method.