Generating fuzzy rules by genetic algorithms

M. Mohammadian, R. J. Stonier

Research output: A Conference proceeding or a Chapter in BookConference contribution

20 Citations (Scopus)

Abstract

A general method is developed to generate fuzzy rules by using Genetic Algorithms (GAs) and a Fuzzy Logic controller (FLC). By using GAs as a learning procedure and a FLC as the system's performance evaluator, the proposed architecture can construct an input-output mapping in the form of fuzzy If-Then rules. The performance of the new architecture is compared with an artificial neural networks controller and pure limited-rule fuzzy rule controller for the truck back-upper problem.

Original languageEnglish
Title of host publicationProceedings of 1994 3rd IEEE International Workshop on Robot and Human Communication
Place of PublicationPiscataway NJ, USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages362-367
Number of pages6
ISBN (Electronic)0780320034
ISBN (Print)07780320026
DOIs
Publication statusPublished - 1994
Externally publishedYes
Event3rd IEEE International Workshop on Robot and Human Communication - Nagoya, Japan
Duration: 18 Jul 199420 Jul 1994

Conference

Conference3rd IEEE International Workshop on Robot and Human Communication
Abbreviated titleRo-Man
CountryJapan
CityNagoya
Period18/07/9420/07/94

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  • Cite this

    Mohammadian, M., & Stonier, R. J. (1994). Generating fuzzy rules by genetic algorithms. In Proceedings of 1994 3rd IEEE International Workshop on Robot and Human Communication (pp. 362-367). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ROMAN.1994.365902