Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Multiple-Valued Fuzzy Approximate Analogical-Reasoning System

  • Turksen, I.B. (Department of Industrial Engineering, Mechanical Engineering, and Computer science University of Toronto) ;
  • Guo, L.Z. (Department of Industrial Engineering, Mechanical Engineering, and Computer science University of Toronto) ;
  • Smith, K.C. (Departments of Electrical and Computer Engineering, Mechanical Engineering, and Computer Science University of Toronto)
  • Published : 1993.06.01
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Abstract

We have designed a multiple-valued fuzzy Approximate Analogical-Reseaning system (AARS). The system uses a similarity measure of fuzzy sets and a threshold of similarity ST to determine whether a rule should be fired, with a Modification Function inferred from the Similarity Measure to deduce a consequent. Multiple-valued basic fuzzy blocks are used to construct the system. A description of the system is presented to illustrate the operation of the schema. The results of simulations show that the system can perform about 3.5 x 106 inferences per second. Finally, we compare the system with Yamakawa's chip which is based on the Compositional Rule of Inference (CRI) with Mamdani's implication.

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