DocumentCode
3465148
Title
Fuzzy expert systems vs. neural networks-truck backer-upper control revisited
Author
Ramamoorthy, P.A. ; Huang, Song
Author_Institution
Dept. of Electr. & Comput. Eng., Cincinnati Univ., OH, USA
fYear
1993
fDate
1-3 Aug. 1993
Firstpage
221
Lastpage
224
Abstract
It is pointed out that by merging the advantages of fuzzy expert systems and neural networks one can arrive at a more powerful yet more flexible system for inferencing and learning. The advantages of fuzzy expert systems are their ability to provide nonlinear mapping through the membership functions and fuzzy rules, and the ability to deal with fuzzy information and incomplete and/or imprecise data. The merger of these two concepts is explained using the truck backer-upper control problem. Novel network architectures obtained by merging these two concepts and simulation results for the truck backer-upper problem using the architecture are shown.<>
Keywords
expert systems; fuzzy logic; neural nets; road vehicles; fuzzy expert systems; fuzzy information; fuzzy rules; imprecise data; incomplete data; inferencing; learning; membership functions; neural networks; nonlinear mapping; truck backer-upper control; Expert systems; Fuzzy logic; Neural networks; Road vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems Engineering, 1991., IEEE International Conference on
Conference_Location
Dayton, OH, USA
Print_ISBN
0-7803-0173-0
Type
conf
DOI
10.1109/ICSYSE.1991.161118
Filename
161118
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