Refinement of the diagnosis process performed with a fuzzy classifier

C. D. Bocaniala, J. Sa Da Costa, V. Palade

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

1 Citation (Scopus)

Abstract

This paper presents a refinement of the diagnosis process performed with a fuzzy classifier. The proposed fuzzy classifier demonstrated high accuracy in recognizing faults. In our previous work, when using this classifier, one single category has been considered for each one of the faults under observation. However, 20 levels of fault strength have been considered for each fault, ranging from small and often unnoticeable effects up to large effects. The present work proposes three categories to be considered for each fault, corresponding to small, medium and respectively large faults. Better diagnosis results are obtained. Moreover, the proposed refinement offers a new insight and more information on the behavior of the faults, that improve the final outcome of the diagnosis process.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems
EditorsMircea Gh. Negoita, Robert J. Howlett, Lakhmi C. Jain
Place of PublicationBerlin
PublisherSpringer
Pages373-379
Number of pages7
Volume3215
ISBN (Electronic)978-3-540-30134-9
ISBN (Print)978-3-540-23205-6
DOIs
Publication statusPublished - 2004
Externally publishedYes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Bocaniala, C. D., Sa Da Costa, J., & Palade, V. (2004). Refinement of the diagnosis process performed with a fuzzy classifier. In M. G. Negoita, R. J. Howlett, & L. C. Jain (Eds.), Knowledge-Based Intelligent Information and Engineering Systems (Vol. 3215, pp. 373-379). Berlin: Springer. https://doi.org/10.1007/978-3-540-30134-9_49