Connectionism for fuzzy learning in rule-based expert systems

  • Fu LiMin
Euzzy Logic and Control
Part of the Lecture Notes in Computer Science book series (LNCS, volume 604)


A novel approach to rule refinement based upon connectionism is presented. This approach is capable of performing rule deletion, rule addition, changing rule quality, and modification of rule strengths. The fundamental algorithm is referred to as the Consistent-Shift algorithm. Its basis for identifying incorrect connections is that incorrect connections will often undergo larger inconsistent weight shift than correct ones during training with correct samples. By properly adjusting the detection threshold, incorrect connections would be uncovered, which can then be deleted or modified. Deletion of incorrect connections and addition of correct connections then translate into various forms of rule refinement just mentioned.


Expert System Neural Network 


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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Fu LiMin
    • 1
  1. 1.Department of Computer and Information SciencesUniversity of FloridaGainesville

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