A new TSK fuzzy modeling approach

Kyoungjung Kim, You Keun Kim, Euntai Kim, Mignon Park

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

4 Citations (Scopus)


In this paper, a new robust TSK fuzzy modeling algorithm is proposed. The proposed algorithm is the modified version of noise clustering algorithm. Various robust approaches to deal with the data containing noise or outliers in real applications were proposed, but most algorithms process clustering of data first and then conduct fuzzy regression. We propose the algorithm that parameters of the premise part and the consequent part are obtained simultaneously. The proposed algorithm shows good performance against noise or outliers. Without adaptation of parameters, the proposed algorithm shows the superior performance over other approaches.

Original languageEnglish
Title of host publication2004 IEEE International Conference on Fuzzy Systems - Proceedings
Number of pages4
Publication statusPublished - 2004
Event2004 IEEE International Conference on Fuzzy Systems - Proceedings - Budapest, Hungary
Duration: 2004 Jul 252004 Jul 29

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584


Other2004 IEEE International Conference on Fuzzy Systems - Proceedings

All Science Journal Classification (ASJC) codes

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


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