About: RBF Networks for function approximation in dynamic modelling     Goto   Sponge   NotDistinct   Permalink

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Description
  • The paper demonstrates the comparison of Monte Carlo simulation algorithm with neural network enhancement in the reliability case study. With regard to process dynamics, we attempt to evaluate the tank system unreliability related to the initiative input parameters setting. The neural network is used in equation coefficients calculation, which is executed in each transient state. Due to the neural networks, for some of the initial component settings we can achieve the results of computation faster than in classical way of coefficients calculating and substituting into the equation.
  • The paper demonstrates the comparison of Monte Carlo simulation algorithm with neural network enhancement in the reliability case study. With regard to process dynamics, we attempt to evaluate the tank system unreliability related to the initiative input parameters setting. The neural network is used in equation coefficients calculation, which is executed in each transient state. Due to the neural networks, for some of the initial component settings we can achieve the results of computation faster than in classical way of coefficients calculating and substituting into the equation. (en)
Title
  • RBF Networks for function approximation in dynamic modelling
  • RBF Networks for function approximation in dynamic modelling (en)
skos:prefLabel
  • RBF Networks for function approximation in dynamic modelling
  • RBF Networks for function approximation in dynamic modelling (en)
skos:notation
  • RIV/61989100:27240/09:00021344!RIV10-MSM-27240___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1M06047)
http://linked.open...iv/cisloPeriodika
  • No.2 (13)
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
  • 338166
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27240/09:00021344
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • dynamic reliability; neural networks (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • US - Spojené státy americké
http://linked.open...ontrolniKodProRIV
  • [58036DFFCD0E]
http://linked.open...i/riv/nazevZdroje
  • Reliability and Risk Analysis: Theory and Applications
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...v/svazekPeriodika
  • 2009
http://linked.open...iv/tvurceVysledku
  • Nedbálek, Jakub
issn
  • 1932-2321
number of pages
http://localhost/t...ganizacniJednotka
  • 27240
is http://linked.open...avai/riv/vysledek of
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