Three new uncertainty bound methods of Karnik-Mendel algorithms

Xinwang Liu, Qian Zhu, Song Guo

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


Karnik-Mendel (KM) algorithms are important tools for the centroid computation or type reduction in the type-2 fuzzy logic. To release the possible computational bottleneck of the iteration of KM algorithms, some uncertainty bound methods are proposed. In the present paper, the current uncertainty bounds are extended and improved with three new uncertainty bound methods for the centroid computation of interval type-2 fuzzy sets. The New uncertainty bound methods can be further improved if some prior information is available or be be improved from the current bound values. Theoretical analysis proves the validity of our new approaches.
Original languageEnglish
Title of host publicationFUZZ-IEEE 2013 - 2013 IEEE International Conference on Fuzzy Systems
Publication statusPublished - 22 Nov 2013
Externally publishedYes
Event2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013 - Hyderabad, India
Duration: 7 Jul 201310 Jul 2013


Conference2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013


  • Karnik-Mendel (KM) algorithms
  • Type-2 fuzzy set and system
  • Uncertainty bound method

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Applied Mathematics
  • Theoretical Computer Science

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