Abstract
Designing a set of fuzzy neural networks can be considered as solving a multi-objective optimization problem. An algorithm for solving the multi-objective optimization problem is presented based on particle swarm optimization through the improvement of the selection manner for global and individual extremum. The search for the Pareto Optimal Set of fuzzy neural networks optimization problems is performed. Numerical simulations for taste identification of tea show the effectiveness of the proposed algorithm.
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Ma, M., Zhang, LB., Ma, J., Zhou, CG. (2006). Fuzzy Neural Network Optimization by a Particle Swarm Optimization Algorithm. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11759966_110
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DOI: https://doi.org/10.1007/11759966_110
Publisher Name: Springer, Berlin, Heidelberg
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