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基于模块化模糊子系统的分层模糊神经网络
刘芳 ; 刘民 ; 吴澄 ; LIU Fang ; LIU Min ; WU Cheng
2010-06-09 ; 2010-06-09
关键词聚类方法 分层模糊神经网络 进化规划 Clustering algorithm Hierarchical fuzzy neural network Evolutionary programming TP183
其他题名Hierarchical Fuzzy Neural Network Based on Module Fuzzy Subsystems
中文摘要提出一种基于模块化模糊子系统的分层模糊神经网络.该分层模糊神经网络基于高斯隶属函数,且功能上等价于一个TSK模糊系统.这种分层神经网络在保留了传统模糊神经网络很多优点的同时有效地抑制了“维数灾”问题,而且在模糊子系统中模糊规则的激活强度有所提高.仿真试验结果表明,该方法能获得更为简洁有效的模糊规则集.; A hierarchical fuzzy neural network based on module fuzzy subsystems (HM-FNNs) is proposed, which is built based on ellipsoidal basis function and is equivalent to a Takagi-Sugeno-Kang fuzzy system functionally. The HM-FNNs not only remains the full benefits of a traditional FNNs but also suppress the effects of the unwanted phenomenon, “the curse of dimensionality”. It also offers one great advantage that all rule fire strengths are strong on average when passing through subsystem layers. The simulation results show that the proposed method can produce the compact and high performance fuzzy rule-base.
语种中文 ; 中文
内容类型期刊论文
源URL[http://hdl.handle.net/123456789/57673]  
专题清华大学
推荐引用方式
GB/T 7714
刘芳,刘民,吴澄,等. 基于模块化模糊子系统的分层模糊神经网络[J],2010, 2010.
APA 刘芳,刘民,吴澄,LIU Fang,LIU Min,&WU Cheng.(2010).基于模块化模糊子系统的分层模糊神经网络..
MLA 刘芳,et al."基于模块化模糊子系统的分层模糊神经网络".(2010).
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