期刊名称：Advances in Computer Science and its Applications
印刷版ISSN：2166-2924
出版年度：2015
卷号：3
期号：1
语种：English
出版社：World Science Publisher
摘要：One major problem in the use of neural networks is the long training time. The purpose of this paper is to demonstrate the optimization of training that occurs with the application of fuzzy logic controller theory to neural networks. The resulting fuzzy-logic-controlled neural network (FLCNN) exhibits a significant cut in the training period. A fuzzy logic system (FLS) is employed to control the learning parameters of a neural network (NN) to reduce the possibility of overshooting during the learning process. Hence, the learning time of the neural network can be shortened. This paper compares the training efficiency and accuracy between a NN and a FLCNN, when they are required to carry out the same assignment. In one application, the training time is reduced by 30%.
关键词：network;Standard Training Shortcomings;fuzzy logic controller
