HYBRID NEURAL NETS CAN BE FUZZY CONTROLLERS AND FUZZY EXPERT-SYSTEMS

被引：21
|
作者：
BUCKLEY, JJ [1 ]
HAYASHI, Y [1 ]
机构：
[1] IBARAKI UNIV,DEPT COMP & INFORMAT SCI,HITACHI,IBARAKI 316,JAPAN
来源：
FUZZY SETS AND SYSTEMS | 1993年 / 60卷 / 02期
关键词：
NEURAL NETWORKS; FUZZY CONTROLLER; FUZZY EXPERT SYSTEMS; HYBRID NEURAL NETWORKS;
D O I：
10.1016/0165-0114(93)90342-F
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Given a discrete fuzzy expert system we show how to construct a hybrid neural net computationally identical to the fuzzy expert system. Given a Sugeno, Mamdani, or expert system type of controller we build a hybrid neural net that is computationally the same as the controller. This improves on previous results that show a (regular) neural net can approximate continuous fuzzy controllers and continuous fuzzy expert systems to any degree of accuracy.
引用
收藏
页码：135 / 142
页数：8
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