A case study of knowledge acquisition

From connectionist learning to an optimized fuzzy knowledge base

M. Mohammadian, X. H. Yu, J. D. Smith

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

4 Citations (Scopus)
3 Downloads (Pure)

Abstract

An automated knowledge acquisition architecture for docking a truck problem is presented. The architecture consists of a neural network controller a fuzzy rule maker, and a fuzzy controller. The neural network controller is used to learn the driving knowledge from trials. The driving knowledge is then extracted by the fuzzy rule maker to form a driving knowledge rule base. The driving knowledge rule base is further optimized using a genetic algorithm. Computer simulations are presented to show the effectiveness of the architecture.

Original languageEnglish
Title of host publicationProceedings of IEEE 2nd International Workshop on Emerging Technologies and Factory Automation
Subtitle of host publicationDesign and Operations of Intelligent Factories, ETFA 1993
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages106-111
Number of pages6
ISBN (Print)0780309853
DOIs
Publication statusPublished - 1993
Externally publishedYes
Event2nd IEEE International Workshop on Emerging Technologies and Factory Automation: Design and Operations of Intelligent Factories, ETFA 1993 - Palm Cove-Cairns, Australia
Duration: 27 Sep 199329 Sep 1993

Conference

Conference2nd IEEE International Workshop on Emerging Technologies and Factory Automation: Design and Operations of Intelligent Factories, ETFA 1993
CountryAustralia
CityPalm Cove-Cairns
Period27/09/9329/09/93

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Cite this

Mohammadian, M., Yu, X. H., & Smith, J. D. (1993). A case study of knowledge acquisition: From connectionist learning to an optimized fuzzy knowledge base. In Proceedings of IEEE 2nd International Workshop on Emerging Technologies and Factory Automation: Design and Operations of Intelligent Factories, ETFA 1993 (pp. 106-111). [396423] IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ETFA.1993.396423