摘要
提出了一种Add-Mult型模糊神经网络模型(AMFNN)，给出了该模型的结构。根据 梯度下降算法，给出了AMFNN模糊神经网络的误差反传学习算法。与6种极具代表性的模糊推 理方法进行比较的结果表明，AMFNN模糊神经网络模型具有推理精度高、适用范围广、泛化 能力强以及实现容易等特点，因而具有广阔的应用前景。
This paper presents a model of Add-Mult fuzzy neural network (AMFNN ) and the models architecture as well. Error back propagation algorithm for AMFN N is presented according to the gradient descent method. The result compared wit h six representative fuzzy inference methods shows that AMFNN has high reasoning precision, wide application scope, strong generalization capability and easy re alization characteristics. Consequently, AMFNN has vast application prospect.
出处
《计算机工程》
CAS
CSCD
北大核心
2003年第21期141-143,148,共4页
Computer Engineering
