Aggregation Operator Based Fuzzy Pattern Classifier Design

Uwe Mönks, Henrik Legind Larsen, Volker Lohweg

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

Abstrakt

This paper presents a novel modular fuzzy pattern classifier design framework for intelligent automation systems, developed on the base of the established Modified Fuzzy Pattern Classifier (MFPC) and allows designing novel classifier models which are hardware-efficiently implementable. The performances of novel classifiers using substitutes of MFPC's geometric mean aggregator are benchmarked in the scope of an image processing application against the MFPC to reveal classification improvement potentials for obtaining higher classification rates.

OriginalsprogEngelsk
TitelMachine learning in real-time applications (MLRTA 09) : In conjunction with 32nd Annual Conference on Artificial Intelligence KI 2009 workshop, Paderborn, September 15th, 2009
RedaktørerVolker Lohweg, Oliver Niggemann
Antal sider8
ForlagInstitut Industrial IT der Hochschule Ostwestfalen-Lippe
Publikationsdato2009
StatusUdgivet - 2009
BegivenhedWorkshop Machine Learning in Real-Time Applications (KI 2009 Workshop, Paderborn, September 15th, 2009) - Paderborn, Tyskland
Varighed: 15 sep. 200918 sep. 2009

Konference

KonferenceWorkshop Machine Learning in Real-Time Applications (KI 2009 Workshop, Paderborn, September 15th, 2009)
LandTyskland
ByPaderborn
Periode15/09/200918/09/2009
NavnLemgoer Schriftenreihe zur industriellen Informationstechnik
Nummer3

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Citationsformater

Mönks, U., Larsen, H. L., & Lohweg, V. (2009). Aggregation Operator Based Fuzzy Pattern Classifier Design. I V. Lohweg, & O. Niggemann (red.), Machine learning in real-time applications (MLRTA 09) : In conjunction with 32nd Annual Conference on Artificial Intelligence KI 2009 workshop, Paderborn, September 15th, 2009 Institut Industrial IT der Hochschule Ostwestfalen-Lippe. Lemgoer Schriftenreihe zur industriellen Informationstechnik, Nr. 3