文献类型：期刊文献

中文题名：基于蚁群聚类算法的模糊神经网络

英文题名：Fuzzy Neural Network Based on Ant Colony Clustering Algorithm

作者：曹晓辛[1];李柠[1];黄道[1]

机构：[1]华东理工大学自动化工程中心,上海200237

年份：2005

卷号：31

期号：2

起止页码：215

中文期刊名：华东理工大学学报（自然科学版）

外文期刊名：Journal of East China University of Science and Technology

收录：CSTPCD;;EI(收录号：2005209110095);Scopus;北大核心:【北大核心2004】；CSCD:【CSCD2011_2012】；

基金：国家863资助课题(2002AA412120)

语种：中文

中文关键词：蚁群算法;聚类算法;模糊神经网络;模糊C-均值聚类(FCM);RBF

外文关键词：ant algorithm; clustering algorithm; fuzzy neural network;fuzzy c-means clustering(FCM); RBF

摘要：提出了一种基于蚁群聚类的模糊神经网络算法,神经网络采用RBF网络结点结构,聚类采用二级结构蚁群聚类算法作为一级聚类而模糊C-均值聚类(FCM)用于二级聚类。将上述聚类方法用于模糊神经网络构建中,仿真结果表明具有并行实时性、聚类能力强的特点。
Fuzzy neural network based on fuzzy C-means clustering algorithm (FCM) is applied widely to the design of modeling and controlling. This paper proposes a fuzzy neural network based on two-stage clustering algorithm in order to determine the fuzzy rules and the number of rules. The neural network based on RBF is constructed using the relationship between the neural network and RBF. The way provides the solve of optimal parameter which consist of parallel just-time, the strong ability of clustering.