Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on the slopes of fuzzy sets

  • Authors:

  • Shyi-Ming Chen;Wen-Chyuan Hsin;Szu-Wei Yang;Yu-Chuan Chang

  • Affiliations:

  • Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC;Department of Education, National Taichung University of Education, Taichung, Taiwan, ROC;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, ROC

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

In this paper, we present a new fuzzy interpolative reasoning method for sparse fuzzy rule-based systems based on the slopes of fuzzy sets. The proposed method can deal with fuzzy rules interpolation involving complex polygonal fuzzy sets with the advantages of simplest calculation and get more reasonable fuzzy interpolative reasoning results. We also make some experiments to compare the fuzzy interpolative reasoning results of the proposed method with the ones of the existing methods. The experimental results show that the proposed method outperforms the existing fuzzy interpolative reasoning methods for sparse fuzzy rule-based systems.