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Description
  • Industrial plants use many different sensors for processes monitoring and controlling. These sensors generate huge amount of data. These data should be used for improving of the quality of semi and final products in each factory. In this paper, we describe processing of two different datasets acquired from a steel-mill factory using three different methods SVM, Fuzzy Rules and Bayesian classification. Moreover, we describe problems of each method with confrontation with real data. Each of the method used works in different algorithm and is not based on the same theory. Their comparison gives a nice review of the real application of these methods.
  • Industrial plants use many different sensors for processes monitoring and controlling. These sensors generate huge amount of data. These data should be used for improving of the quality of semi and final products in each factory. In this paper, we describe processing of two different datasets acquired from a steel-mill factory using three different methods SVM, Fuzzy Rules and Bayesian classification. Moreover, we describe problems of each method with confrontation with real data. Each of the method used works in different algorithm and is not based on the same theory. Their comparison gives a nice review of the real application of these methods. (en)
Title
  • Prediction of multi-class industrial data
  • Prediction of multi-class industrial data (en)
skos:prefLabel
  • Prediction of multi-class industrial data
  • Prediction of multi-class industrial data (en)
skos:notation
  • RIV/61989100:27740/13:86088855!RIV14-MSM-27740___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0070), P(EE.2.3.20.0073), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 98594
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27740/13:86088855
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Support vector machin; Quality prediction; Industrial data; Fuzzy rules; Data processing; Bayesian classification (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [50EFE7738C9A]
http://linked.open...v/mistoKonaniAkce
  • Xi'an
http://linked.open...i/riv/mistoVydani
  • Danvers
http://linked.open...i/riv/nazevZdroje
  • Proceedings - 5th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2013
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Krömer, Pavel
  • Platoš, Jan
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE
https://schema.org/isbn
  • 978-0-7695-4988-0
http://localhost/t...ganizacniJednotka
  • 27740
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