广东工业大学学报Issue(1)：36-39,4.DOI:10.3969/j.issn.1007-7162.2014.01.007
一种粒子群-Mamdani 模糊神经网络的参数优化新算法
A Novel Parameter Optimization Algorithm for Mamdani Fuzzy Neural Networks Based on PSO
摘要
Abstract
In order to avoid local optimum of Mamdani model parameter optimization , a novel algorithm for Mamdani neural network was proposed .The initial parameters of Mamdani Fuzzy Neural Network ( FNN) were generated by Fuzzy C-means clustering , based on PSO , and then optimized by using PSO . Finally , Gradient descent method was adopted for further optimizing the parameters so that the fuzzy rules could be automatically adjusted , modified and improved .Numerical experiments show that the presented algorithm improves the approximation ability of Mamdani FNN .关键词
粒子群算法/模糊聚类/模糊规则库/Mamdani模糊神经网络/优化/梯度下降法Key words
particle swarm optimization(PSO)/fuzzy c-means clustering(FCM)/fuzzy rules/Mamdani neural networks/optimization/gradient descent method分类
信息技术与安全科学引用本文复制引用
姚蕾..一种粒子群-Mamdani 模糊神经网络的参数优化新算法[J].广东工业大学学报,2014,(1):36-39,4.基金项目
国家自然科学基金资助项目 （）
