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文中提出了将模糊聚类与梯度算法相结合的一种改进的训练模糊神经网络的混合型算法．模拟结果表明，模糊神经网络可以成功地用于时间序列的预测，模糊神经网络的训练速度与模拟精度都优于传统多层ＢＰ网络．
In this paper, an improved hybrid algorithm for training fuzzy neural networks is proposed by combining fuzzy clustering and gradient algorithms. The simulation results show that the fuzzy neural network can be successfully used to predict the time series. The training speed and the simulation accuracy of the fuzzy neural network are superior to the traditional multi-layer BP network.