0314025 - ÚTIA 2009 RIV US eng C - Konferenční příspěvek (zahraniční konf.)
Hofman, Radek - Pecha, Petr
Data Assimilation of Model Predictions of Long-Time Evolution of CS-137 Deposition on Terrain.
[Asimilace modelu dlouhodobého časového vývoje depozice Cs-137 na terénu.]
Proceeding of the IEEE International Geoscience & Remote Sensing Symposium 2008. Boston: IEEE, 2008, s. 1-4. ISBN N.
[IEEE International Geoscience & Remote Sensing Symposium 2008. Boston (US), 06.07.2008-11.07.2008]
Grant CEP: GA ČR(CZ) GA102/07/1596
Výzkumný záměr: CEZ:AV0Z10750506
Klíčová slova: data assimilation * marginalized particle filter * estimation * covariance structure
Kód oboru RIV: DI - Znečištění a kontrola vzduchu
Web výsledku:
http://library.utia.cas.cz/separaty/2008/AS/hofman-data%20assimilation%20of%20model%20predictions%20of%20long-time%20evolution%20of%20cs-137%20deposition%20on%20terrain.pdf

The paper presents a scheme for estimation of spatio-temporal evolution of a quantity with unknown model error based on LU model. Solution of LU model is efficient and easy to implementation even for high dimensional problems. Model error is assumed to be uniformly distributed and it is estimated upon measured and modeled values. Methods of linear programming are applied to the problem. The main contribution of this paper is application of general LU estimation algorithm to the linear--uniform problem with unknown model error magnitude. Methodology is demonstrated on the problem of modeling of spatio--temporal evolution of groundshine--dose from radionuclides deposited on terrain in long-time horizon. Achieved results and the methodology is compared to the results obtained by an approach based on the MPF algorithm. The advantages of particular methods are conclud

Článek presentuje schéma pro odhad spatio-temporálního vývoje kvantity s neznámým chybovým modelem založeným na LU modelu.
Trvalý link: http://hdl.handle.net/11104/0164665