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Automatic fuzzy rule extraction based on particle swarm optimization

机译:基于粒子群优化的自动模糊规则提取

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摘要

The extraction of fuzzy rules is always a difficult problem to fuzzy system. We have proposed a pruning algorithm to optimize fuzzy neural network based on particle swarm optimization algorithm. It can evolve both the fuzzy neural network's topology and weighting parameters. In a real problem, it can automatically obtain the near-optimal structure of fuzzy neural network according to the requirements. The experiment has proved that the method is applicable and efficient.
机译:模糊规则的提取始终是模糊系统的难题。我们提出了一种修剪算法来优化基于粒子群优化算法的模糊神经网络。它可以发展模糊神经网络的拓扑和加权参数。在一个真正的问题中,它可以根据要求自动获得模糊神经网络的近乎最佳结构。实验证明了该方法适用和有效。

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