Fuzzy number neural networks

被引：15
|
作者：
Dunyak, J [1 ]
Wunsch, D
机构：
[1] Texas Tech Univ, Dept Math, Lubbock, TX 79409 USA
[2] Texas Tech Univ, Dept Elect Engn, Lubbock, TX 79409 USA
来源：
FUZZY SETS AND SYSTEMS | 1999年 / 108卷 / 01期
关键词：
fuzzy numbers; neural networks; learning;
D O I：
10.1016/S0165-0114(97)00339-4
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper presents a practical algorithm for training neural networks with fuzzy number weights, inputs, and outputs. Typically, fuzzy number neural networks are difficult to train because of the many a-cut constraints implied by the fuzzy weights. A transformation is used to eliminate these constraints and allow use of standard unconstrained optimization methods. The algorithm is demonstrated on a three-layer network. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：49 / 58
页数：10
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