Inverse Problems for Nonlinear Systems via Bayesian Parameter Identification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F12%3A00199943" target="_blank" >RIV/68407700:21110/12:00199943 - isvavai.cz</a>
Result on the web
<a href="http://www.siam.org/meetings/uq12/uq12_abstracts.pdf" target="_blank" >http://www.siam.org/meetings/uq12/uq12_abstracts.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Inverse Problems for Nonlinear Systems via Bayesian Parameter Identification
Original language description
Inverse problems are important in engineering science and appear very frequently such as for example in estimation of material porosity and properties describing irreversible behaviour, control of high-speed machining processes etc. At present, most of identification procedures have to cope with ill-possedness as the problems are often considered in a deterministic framework. However, if the parameters are modelled as random variables the process of obtaining more information through experiments in a Bayesian setting becomes well-posed. In this manner the Bayesian information update can be seen as a minimisation of variance. In this work we use the functional approximation of uncertainty and develop a purely deterministic procedure for the updating process. This is then contrasted to a fully Bayesian update based on Markov chain Monte Carlo sampling on a few numerical nonlinear examples. Examples are based on plasticity and nonlinear diffusion models.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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