• 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