Realizing Intelligent Control Systems by combining Fuzzy Logic and Neural Networks

被引：0
|
作者：
Ashford, R [1 ]
机构：
[1] Lockheed Martin Aeronaut Marietta, Marietta, GA 30063 USA
来源：
IC-AI'2000: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 1-III | 2000年
关键词：
Intelligent Control; Fuzzy Logic; Neural Networks;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Intelligent Control Systems - the fusion of intelligence and automatic control theory - are revolutionizing man's ability to control his environment. For their full potential to be reached, more research on the synthesis of these technologies is needed. The control system architecture chosen for a particular problem is critical for a successful outcome. This paper explores architectural considerations for Intelligent Control System implementations using Fuzzy Logic and Neural Networks. Strengths and weaknesses of each are noted. Different architectures utilizing these technologies in isolated and integrated manners are reviewed. Finally, architecture recommendations and areas of further research are presented.
引用
收藏
页码：883 / 889
页数：7
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