摘要
本文将模糊逻辑与神经网络相结合,对一种能表达知识规则的模糊神经系统模型进行研究,给出了该模糊神经系统的结构和学习算法.并将其用于105组稻米香数据的数值实验,仿真结果表明,该模型的性能优于一般模糊系统,从而表明了这一模型的有效性.
A study on a new model of fuzzy neural systems(FNS) is made with the combination of fuzzy logic and neural networks. The proposed model is able to express rules of fuzzy knowledge (fuzzy if -then rules). The architecture and learning algorithme of the model are also proposed. Numerical experiment on 105 pairs of rice taste data is presented. Simulation results indicates the proposed model has better performance than that of general fuzzy systems.
出处
《系统工程》
CSCD
1999年第4期61-64,32,共5页
Systems Engineering
基金
中船总公司国防预研基金资助课题
关键词
模糊集
人工神经网络
模糊系统
Fuzzy set, Artificial meural networks, Fuzzy systems
