Differential evolution algorithem design for fuzzy neural network

Differential evolution is a novel method to search global optimum. A new pruning algorithm for solving the fuzzy neural network design problem is proposed based on differential evolution with division of work. Based on the proposed algorithm, an optimal and efficient fuzzy neural network structure can be constructed by the requirements. Numerical simulations show the effectiveness of the proposed algorithm.