Parameter Identification in Initial Value Problems for Nonlinear Ordinary Differential Equations

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Parameter Identification in Initial Value Problems for Nonlinear Ordinary Differential Equations

Popis výsledku v původním jazyce

Nonlinear initial value problems (IVPs) for ordinary differential equations are considered. As a representative, a cement hydration model is chosen. The model equation depends on a few parameters that are to be identified on the basis of hydration-related measurements at a sequence of time points. This is done through the minimization of a cost function defined as the sum of squared differences between the measured values and the model response at the same time points. To minimize the cost function, a gradient based algorithm is used. The gradient of the cost function can be calculated either by numerical differentiation or via solving auxiliary initial value problem. The minimization algorithm tends to find a local minimum, therefore it is run from different starting points to increase the chance of finding the global minimum. Algorithms are coded in Matlab and Matlab IVP solvers as well as Matlab Optimization Toolbox and Symbolic Math Toolbox are utilized. The latter makes the deriva

Název v anglickém jazyce

Parameter Identification in Initial Value Problems for Nonlinear Ordinary Differential Equations

Popis výsledku anglicky

Nonlinear initial value problems (IVPs) for ordinary differential equations are considered. As a representative, a cement hydration model is chosen. The model equation depends on a few parameters that are to be identified on the basis of hydration-related measurements at a sequence of time points. This is done through the minimization of a cost function defined as the sum of squared differences between the measured values and the model response at the same time points. To minimize the cost function, a gradient based algorithm is used. The gradient of the cost function can be calculated either by numerical differentiation or via solving auxiliary initial value problem. The minimization algorithm tends to find a local minimum, therefore it is run from different starting points to increase the chance of finding the global minimum. Algorithms are coded in Matlab and Matlab IVP solvers as well as Matlab Optimization Toolbox and Symbolic Math Toolbox are utilized. The latter makes the deriva

Druh

O - Ostatní výsledky

CEP obor

BA - Obecná matematika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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