Adaptive scheduling of optimization algorithms in the construction of interpolative fuzzy systems

Krisztián Balázs, L. Kóczy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper presents an adaptive scheduling approach applied for constructing interpolative fuzzy rule based systems. This is a continuation of our preceding work, where the same approach was used for dense fuzzy rule bases.

Original languageEnglish
Title of host publicationIEEE International Conference on Fuzzy Systems
DOIs
Publication statusPublished - 2013
Event2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013 - Hyderabad, India
Duration: Jul 7 2013Jul 10 2013

Other

Other2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013
CountryIndia
CityHyderabad
Period7/7/137/10/13

Fingerprint

Adaptive Scheduling
Fuzzy Rule Base
Fuzzy Rule-based Systems
Fuzzy rules
Fuzzy systems
Fuzzy Systems
Continuation
Optimization Algorithm
Scheduling
Knowledge based systems

Keywords

  • Adaptive scheduling of optimization algorithms
  • Fuzzy rule based knowledge extraction
  • Interpolative fuzzy systems

ASJC Scopus subject areas

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

Cite this

Adaptive scheduling of optimization algorithms in the construction of interpolative fuzzy systems. / Balázs, Krisztián; Kóczy, L.

IEEE International Conference on Fuzzy Systems. 2013. 6622555.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Balázs, K & Kóczy, L 2013, Adaptive scheduling of optimization algorithms in the construction of interpolative fuzzy systems. in IEEE International Conference on Fuzzy Systems., 6622555, 2013 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2013, Hyderabad, India, 7/7/13. https://doi.org/10.1109/FUZZ-IEEE.2013.6622555
Balázs, Krisztián ; Kóczy, L. / Adaptive scheduling of optimization algorithms in the construction of interpolative fuzzy systems. IEEE International Conference on Fuzzy Systems. 2013.
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