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一类三层前向折线模糊神经网络的构造
引用本文:李丹,孙刚,王贵君. 一类三层前向折线模糊神经网络的构造[J]. 东北师大学报(自然科学版), 2012, 44(3): 55-59
作者姓名:李丹  孙刚  王贵君
作者单位:1. 天津师范大学数学科学学院,天津,300387
2. 大连海事大学轮机工程学院,辽宁大连,116026
基金项目:国家自然科学基金资助项目(60974144)
摘    要:为克服模糊数运算的复杂性引入了折线模糊数的概念,并应用其优良性质和折线模糊值函数的表示定理,通过插值神经网络的构造方法获得了一类三层前向折线模糊神经网络,证明了该折线模糊神经网络是连续折线模糊值函数的泛逼近器.

关 键 词:折线模糊数  折线模糊值函数  插值神经网络  折线模糊神经网络  泛逼近

Construction of a class of three-layered feedforward polygonal fuzzy neural network
LI Dan , SUN Gang , WANG Gui-jun. Construction of a class of three-layered feedforward polygonal fuzzy neural network[J]. Journal of Northeast Normal University (Natural Science Edition), 2012, 44(3): 55-59
Authors:LI Dan    SUN Gang    WANG Gui-jun
Affiliation:1(1.School of Mathematics Sciences,Tianjin Normal University,Tianjin 300387,China; 2.Marine Engineering College,Dalian Maritime University,Dalian 116026,China)
Abstract:The polygonal fuzzy numbers are introduced to overcome the complexity of fuzzy numbers’ operations,and then,by means of good properties of polygonal fuzzy numbers and the representation theorem of polygonal fuzzy numbers valued functions,the three-layer polygonal fuzzy neural networks are constructed through the constructing methods of interpolation neural networks.Finally,the approximation of the class of polygonal fuzzy neural networks with respect to the continuous polygonal fuzzy valued functions is proved.
Keywords:polygonal fuzzy numbers  polygonal fuzzy valued functions  interpolation neural networks  polygonal fuzzy neural networks  approximation
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