摘要
本文在Ｍａｍｄａｎｉ模糊推理法的基础上，给出了改进的模糊加权型推理法—广义模糊加权型推理法．构造了一种基于广义模糊加权型推理法的模糊神经网络，利用遗传算法来训练网络、优化隶属度函数，根据训练后的网络权值可以自动抽取出模糊规则，并通过模拟实验验证了网络模型和算法的有效性．
This paper gives an improving fuzzy weighted reasoning method according to 'Mamdani' reasoning method.A fuzzy neural network is developed based on the improving fuzzy weighted reasoning method . The training of network weights and optimization of membership functions are conducted employing genetic algorithms.Fuzzy rules can be obtained according to the weights of the network.The availability of the network model and the algorithm are examined by simulated tests.
出处
《小型微型计算机系统》
CSCD
北大核心
1999年第4期275-280,共6页
Journal of Chinese Computer Systems
基金
国家自然科学基金
关键词
模糊神经网络
遗传算法
天气预报
模糊推理法
Artificial neural network Fuzzy neural network Genetic algorithms Weather forecast
