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The Optimization of Fuzzy Neural Network Based on Artificial Fish Swarm Algorithm

机译:基于人工鱼群算法的模糊神经网络优化

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摘要

To better solve the optimization problem of fuzzy neural network (FNN), a kind of method based on artificial fish swarm algorithm (AFSA) is proposed in this paper. Aiming at the structure optimization problem of FNN, AFSA-FNN1 is established and realizes the simplification of fuzzy rules. Aiming at the parameter optimization problem of FNN, AFSA-FNN2 is built and realizes the acquisition of parameters of membership function (MF) automatically. The proposed method uses for path planning of the robot, simulation results show that the optimized FNN can enhance the smoothness of the path.
机译:为了更好地解决模糊神经网络(FNN)的优化问题,提出了一种基于人工鱼群算法(AFSA)的方法。针对FNN的结构优化问题,建立了AFSA-FNN1,实现了模糊规则的简化。针对FNN的参数优化问题,构建了AFSA-FNN2并自动实现隶属度函数(MF)的参数获取。该方法用于机器人的路径规划,仿真结果表明,优化的神经网络可以增强路径的平滑度。

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