Feature Selection with Fuzzy Entropy to Find Similar Cases

A3 Bokavsnitt, kapitel i forskningsböcker


Interna författare/redaktörer


Publikationens författare: József Mezei, Juan Antonio Morente-Molinera, Christer Carlsson
Redaktörer: Mo Jamshidi, Vladik Kreinovich, Janusz Kacprzyk
Förläggare: Springer International Publishing
Publiceringsår: 2014
Förläggare: Springer
Moderpublikationens namn: Advance Trends in Soft Computing
Seriens namn: Studies in Fuzziness and Soft Computing
Volym: 312
Artikelns första sida, sidnummer: 383
Artikelns sista sida, sidnummer: 390
ISBN: 978-3-319-03673-1
eISBN: 978-3-319-03674-8
ISSN: 1434-9922


Abstrakt

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.

Senast uppdaterad 2019-13-11 vid 04:09