一种改进的模糊调节神经网络及其应用

针对具有相同激励函数的隐层神经元非线性表达能力较差的情况,提出了一种改进的模糊调节神经网络,并利用遗传算法进行训练。该模糊调节神经网络包括模糊神经网络和三层前馈神经网络2部分,通过模糊神经网络间接调整前馈神经网络隐层激励函数参数,并用遗传算法同时对模糊调节神经网络的权值和模糊神经网络参数进行训练,从而增强了网络的表达能力。将模糊调节神经网络用于非线性量化因子模糊控制器参数的整定仿真结果表明,改进的神经网络比传统的神经网络拥有更大的自由度,具有更强的非线性表现能力,从而使非线性量化因子模糊控制系统具有更好的控制性能。

Improved fuzzy-tuned neural network and its application

For the nonlinearity of neural network with same activation functions in all the hidden nodes is limited,this paper presents a fuzzy-tuned neural network,which is trained by genetic algorithm(GA).The fuzzy-tuned neural network consists of a neural-fuzzy network and a feed-forward neural network.The neural-fuzzy network modifies some of the parameters of the three-layer feed-forward neuron network.All the connecting weighting coefficients and some parameters of the fuzzy-tuned neural network are trained by G...