Feature Selection with Fuzzy Entropy to Find Similar Cases

Jozsef Mezei, Juan Antonio Morente-Molinera, Christer Carlsson

    Research output: Chapter in Book/Conference proceedingChapterScientificpeer-review

    7 Citations (Scopus)

    Abstract

    Process interruptions are carried out either automatically by monitoring and control systems that react to deviations from standards or by operators reacting to anomalies or incidents. Process interruptions in (very) large production systems are difficult to trace and to deal with; an extended stop is also very costly and solutions are sought to find an effective support technology to minimize the number of involuntary process interruptions. Feature selection is intended to reduce the complexity of handling the interactions of numerous factors in large process systems and to help find the best ways to handle process interruptions. We show that feature selection can be carried out with fuzzy entropy and interval-valued fuzzy sets.
    Original languageUndefined/Unknown
    Title of host publicationAdvance Trends in Soft Computing
    EditorsMo Jamshidi, Vladik Kreinovich, Janusz Kacprzyk
    PublisherSpringer
    Pages383–390
    ISBN (Electronic)978-3-319-03674-8
    ISBN (Print)978-3-319-03673-1
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA3 Part of a book or another research book

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