0460818 20240103212415.120160719235959.9 8 s. E cav_un_epca*0460817978-88-9035-745-9357-364ToulouseiEMSs2016 Source term estimation Variational Bayes inference Gamma dose rate measurement CVX optimization toolbox Covariance matrix model cav_un_auth*0267768 Adaptivní systémy Department of Adaptive Systems AS AS Department of Adaptive Systems Tichý Ondřej UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101207 Adaptivní systémy Department of Adaptive Systems AS AS Department of Adaptive Systems Šmídl Václav UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0228606 Adaptivní systémy Department of Adaptive Systems AS AS Department of Adaptive Systems Hofman Radek UTIA-B CZ Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2016/AS/tichy-0460818.pdf cav_un_auth*0318110 7F14287 GA MŠk CZ Detection of release of an atmospheric pollutant is a problem of interest in environmental sciences. We are concerned with estimation of unknown source term of the release. Formally, the problem is formulated as a linear model where measurements are explained using source-receptor-sensitivity matrix obtained from atmospheric transport model and source term vector which has to be estimated. Specifically, we estimate the release of radioactivity from measurements of gamma dose rate (GDR). The problem of isolation of activity of individual nuclides is poorly conditioned. We propose a probabilistic model with the prior information on intervals of nuclide ratios. The model parameters are estimated using the Variational Bayes method. The proposed algorithm is tested on simulated scenario with 16 nuclides and compared with state-of-the-art optimization approaches. cav_un_auth*0331607 The 8th International Congress on Environmental Modelling and Software (iEMSs) 10.07.2016-14.07.2016 Toulouse FR BB 2017 3 PR http://hdl.handle.net/11104/0261530 S 2016 cav_un_epca*0460817 Proceedings of the 8th International Congress on Environmental Modelling and Software (iEMSs) 978-88-9035-745-9 357 364 Toulouse iEMSs 2016