α-cut fuzzy control charts for linguistic data

Murat Gülbay, Cengiz Kahraman, Da Ruan

    Research outputpeer-review

    Abstract

    The major contribution of fuzzy set theory is its capability of representing vague data. Fuzzy logic offers a systematic base in dealing with situations that are ambiguous or not well defined. In the literature, there exist some fuzzy control charts developed for linguistic data that are mainly based on membership and probabilistic approaches. In this article, α-cut control charts for attributes are developed. This approach provides the ability of determining the tightness of the inspection by selecting a suitable α-level: The higher α the tighter inspection. The article also presents a numerical example and interprets and compares other results with the approaches developed previously.

    Original languageEnglish
    Pages (from-to)1173-1195
    Number of pages23
    JournalInternational Journal of Intelligent Systems
    Volume19
    Issue number12
    DOIs
    StatePublished - Dec 2004

    ASJC Scopus subject areas

    • Software
    • Theoretical Computer Science
    • Human-Computer Interaction
    • Artificial Intelligence

    Cite this