FUN: optimization of fuzzy rule based systems using neural networks

Author

Sulzberger, Sandra M. ; Tschichold-Gürman, Nadine N. ; Vestli, Sjur J.

Author_Institution

ETH Zurich, Switzerland

fYear

1993

fDate

1993

Firstpage

312

Abstract

A method for optimization of fuzzy rule based systems using neural networks is described. A neural network model with special neurons has been developed so that the translation of fuzzy rules and membership functions into the network is possible. The performance of this network, and hence the quality of the original rule base, is then improved by training the network using a combination of neural network learning algorithms. The optimized rules and membership functions can be extracted from the net and used in normal fuzzy inference tools. This net has been tested on the WallJumperOver and the problem of local navigation for mobile robots

Keywords

fuzzy control; learning (artificial intelligence); mobile robots; navigation; neural nets; WallJumperOver; fuzzy inference tools; fuzzy rule based systems; learning algorithms; local navigation; membership functions; mobile robots; neural networks; Fuzzy neural networks; Fuzzy systems; Inference algorithms; Knowledge based systems; Mobile robots; Navigation; Neural networks; Neurons; Optimization methods; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1993., IEEE International Conference on

Conference_Location

San Francisco, CA

Print_ISBN

0-7803-0999-5

Type

conf

DOI

10.1109/ICNN.1993.298575

Filename

298575