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Description
  • In the sevens part of the series, the identification of the static characteristics of the nonlinear system is presented. The design of the training and of the testing set and the selection of the ANN topology is described. Further, the calculation of the training and of the inertia coefficients is performed. Two plants were analysed: the plant with the quadratic static characteristics and the bioreactor with the complex static characteristic. Because of the purpose, program in MATLAB was set up. The results obtain showed requirement of the individual access to identify any analysed plant.
  • In the sevens part of the series, the identification of the static characteristics of the nonlinear system is presented. The design of the training and of the testing set and the selection of the ANN topology is described. Further, the calculation of the training and of the inertia coefficients is performed. Two plants were analysed: the plant with the quadratic static characteristics and the bioreactor with the complex static characteristic. Because of the purpose, program in MATLAB was set up. The results obtain showed requirement of the individual access to identify any analysed plant. (en)
  • V příspěvku je popsán postup identifikace statické charakteristiky nelineárního systému s použitím neuronové sítě (NS). Je popsána tvorba trénovací a testovací množiny, výběr topologie NS, počtu epoch trénování a určení parametrů učení (koeficientu učení a koeficientu setrvačnosti). Byly zkoumány dvě soustavy, soustava s kvadratickou statickou charakteristikou a bioreaktor se složitou statickou charakteristikou. Za tímto účelem byl sestaven simulační program v MATLABu. Získané výsledky ukázaly na potřebu individuálního přístupu k identifikaci každé analyzované soustavy. (cs)
Title
  • Identification of the static plant by means of the neural network
  • Identifikace statické soustavy použitím neuronových sití (cs)
  • Identification of the static plant by means of the neural network (en)
skos:prefLabel
  • Identification of the static plant by means of the neural network
  • Identifikace statické soustavy použitím neuronových sití (cs)
  • Identification of the static plant by means of the neural network (en)
skos:notation
  • RIV/00216275:25530/07:00005206!RIV08-MSM-25530___
http://linked.open.../vavai/riv/strany
  • 130
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM0021627505)
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
  • 425316
http://linked.open...ai/riv/idVysledku
  • RIV/00216275:25530/07:00005206
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • static systems; artificial neural network (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [7F8F64578DEC]
http://linked.open...v/mistoKonaniAkce
  • Štrbské Pleso, Higs Tatras, Slovak Republic
http://linked.open...i/riv/mistoVydani
  • Bratislava, Slovak Republic
http://linked.open...i/riv/nazevZdroje
  • Proceedings 16th International Conference on Process Control ´07
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Taufer, Ivan
  • Drábek, Oldřich
  • Seidl, Pavel
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Slovenská technická univerzita v Bratislave
https://schema.org/isbn
  • 978-80-227-2677-1
http://localhost/t...ganizacniJednotka
  • 25530
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