Small-sample probabilistic simulation software tool Freet

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F15%3APU114893" target="_blank" >RIV/00216305:26110/15:PU114893 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Small-sample probabilistic simulation software tool Freet

Popis výsledku v původním jazyce

The objective of the paper is to present methods and software for the efficient statistical, sensitivity and reliability assessment of infrastructure. A special attention is devoted to small-sample simulation techniques which have been developed for theanalysis of computationally intensive problems. The paper shows the possibility of "randomizing" computationally intensive problems in the sense of the Monte Carlo type simulation. In order to keep the number of required simulations at an acceptable level, optimized Latin Hypercube Sampling is utilized. The technique is used for simulation of random variables and random fields. Sensitivity analysis is based on nonparametric rank-order correlation coefficients. Statistical correlation is imposed by the stochastic optimization technique ? simulated annealing. A hierarchical sampling approach has been developed for the extension of the sample size in Latin Hypercube Sampling, enabling the addition of simulations to a current sample set whi

Název v anglickém jazyce

Small-sample probabilistic simulation software tool Freet

Popis výsledku anglicky

The objective of the paper is to present methods and software for the efficient statistical, sensitivity and reliability assessment of infrastructure. A special attention is devoted to small-sample simulation techniques which have been developed for theanalysis of computationally intensive problems. The paper shows the possibility of "randomizing" computationally intensive problems in the sense of the Monte Carlo type simulation. In order to keep the number of required simulations at an acceptable level, optimized Latin Hypercube Sampling is utilized. The technique is used for simulation of random variables and random fields. Sensitivity analysis is based on nonparametric rank-order correlation coefficients. Statistical correlation is imposed by the stochastic optimization technique ? simulated annealing. A hierarchical sampling approach has been developed for the extension of the sample size in Latin Hypercube Sampling, enabling the addition of simulations to a current sample set whi

Druh

O - Ostatní výsledky

CEP obor

JM - Inženýrské stavitelství

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů