中山大学学报（自然科学版）Issue(3)：26-29,35,5.DOI:10.13471/j.cnki.acta.snus.2015.03.005
分级在线自组织学习的 GD-FNN 算法研究
Research on Online Self-Organizational Learning GD-FNN Algorithm by Grading
摘要
Abstract
General dynamic fuzzy neural network (GD-FNN)algorithm is proposed based on the elliptic basis function (EBF).Fuzzy rules generated from the algorithm are intelligibility.It can be used as a modeling tool.and a tool of knowledge extraction.Because of a novel on-line parameter allocation mecha-nism for allevialing the random selection in initialization without relation to different input variable range, the proposed GD-FNN based on fuzzy ε-completeness is more easy to construct a good fuzzy system in per-formance.The simulation program is also developed based on the GD-FNN algorithm and ideal results are achieved by simulation in specific design case.关键词
广义动态模糊神经网络/动态模糊神经网络/径向基函数/椭圆基函数Key words
generalized dynamic fuzzy neural network(GD-FNN)/dynamic fuzzy neural network(D-FNN)/radial basis function(RBF)/elliptic basis function(EBF)分类
信息技术与安全科学引用本文复制引用
左军,周灵,孙亚民..分级在线自组织学习的 GD-FNN 算法研究[J].中山大学学报（自然科学版）,2015,(3):26-29,35,5.基金项目
广东省自然科学基金资助项目 （）
