"1"^^ . "27240" . . . . "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." . "RBF Networks for function approximation in dynamic modelling" . "Reliability and Risk Analysis: Theory and Applications" . . "2009" . "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 . . "RBF Networks for function approximation in dynamic modelling"@en . . "RIV/61989100:27240/09:00021344!RIV10-MSM-27240___" . "RIV/61989100:27240/09:00021344" . "160"^^ . "P(1M06047)" . "Nedb\u00E1lek, Jakub" . "338166" . . "dynamic reliability; neural networks"@en . "1"^^ . . . "RBF Networks for function approximation in dynamic modelling" . . "US - Spojen\u00E9 st\u00E1ty americk\u00E9" . . "1932-2321" . "[58036DFFCD0E]" . "No.2 (13)" . . . "RBF Networks for function approximation in dynamic modelling"@en . .