DocumentCode
3565899
Title
A neural network model for learning rule-based systems
Author
Fu, LiMin
Author_Institution
Dept. of Comput. & Inf. Sci., Florida Univ., Gainesville, FL, USA
Volume
1
fYear
1992
Firstpage
343
Abstract
Knowledgetron, a novel intelligent system which derives rule-based expert systems from neural networks trained by a special computational model, is described. The knowledge of such neural networks is extracted and represented as production rules. The main consideration is that the generated rule-based system perform as well as the original neural network. The system consists of two coupled components. One is the KTBP trainer, which is applied to a multilayer neural network for learning from the data. The trained neural network is translated into a rule-based system by the second component, the KT translator. The feasibility and validity of Knowledgetron have been demonstrated on both small and large neural networks for practical applications
Keywords
knowledge acquisition; knowledge based systems; learning systems; neural nets; KT translator; KTBP trainer; Knowledgetron; computational model; expert systems; learning rule-based systems; neural network model; production rules; Computational intelligence; Computational modeling; Computer networks; Data mining; Expert systems; Intelligent networks; Intelligent systems; Knowledge based systems; Multi-layer neural network; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1992. IJCNN., International Joint Conference on
Print_ISBN
0-7803-0559-0
Type
conf
DOI
10.1109/IJCNN.1992.287188
Filename
287188
Link To Document