Interpolative reasoning approach to sparse general type-2 fuzzy rules based on the reduced grid representation

Long Thanh Ngo, Minh Ngoc Vu, Kaoru Hirota

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Interpolative reasoning is one of the most interested problems with various approaches for type-1 fuzzy sets, interval type-2 fuzzy sets, recently. However, the related methods have not mentioned general type-2 fuzzy sets yet because of their computational complexity. The paper deals with an approach to representation theorem of general type-2 fuzzy sets using the reduced grid. A computational schema for interpolative reasoning of sparse general type-2 fuzzy rules is also introduced. This schema is not depended on the shape of membership functions. Beside, the parallelizing schema for GPU platform is proposed to speedup the algorithms. The proposed methods are implemented on both of GPU and CPU platforms with various membership functions.

Original languageEnglish
Title of host publication2013 International Conference on Soft Computing and Pattern Recognition, SoCPaR 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages72-78
Number of pages7
ISBN (Electronic)9781479934003
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 International Conference on Soft Computing and Pattern Recognition, SoCPaR 2013 - Hanoi, Viet Nam
Duration: 15 Dec 201318 Dec 2013

Publication series

Name2013 International Conference on Soft Computing and Pattern Recognition, SoCPaR 2013

Conference

Conference2013 International Conference on Soft Computing and Pattern Recognition, SoCPaR 2013
Country/TerritoryViet Nam
CityHanoi
Period15/12/1318/12/13

Keywords

  • GPU parallel computing
  • Interpolative reasoning
  • general type-2 fuzzy sets
  • sparse fuzzy rule

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