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Reasoning with truth values on compacted fuzzy chained rules.

A J Bugarin1, S Barro

  • 1Dept. of Electron., Santiago de Compostela Univ.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|February 8, 2008
PubMed
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This study introduces a novel method for executing fuzzy knowledge bases (FKBs) using rule chaining and forward reasoning. The approach enables efficient computation by performing operations a priori, saving significant processing time.

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Fuzzy Logic

Background:

  • Fuzzy knowledge bases (FKBs) require efficient execution methods for rule chaining.
  • Existing inference processes can be complex and dependent on specific variable universes of discourse.

Purpose of the Study:

  • To develop a method for executing FKBs independent of variable universes of discourse.
  • To enable homogeneous treatment of variables within FKBs.
  • To optimize computation time for rule chaining in FKBs.

Main Methods:

  • Utilizing forward reasoning functions derived from the compositional rule of inference.
  • Interpreting rule execution as the propagation of linguistic truth values.
  • Analyzing the process in control systems and expert systems applications.

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Main Results:

  • The proposed method allows rule execution in the truth space, independent of variable definitions.
  • A compaction mechanism is presented for a priori operation execution.
  • Significant computation time savings are achieved.

Conclusions:

  • The developed method provides an efficient and homogeneous approach to executing fuzzy knowledge bases.
  • The compaction mechanism offers practical advantages in terms of computational efficiency for control and expert systems.