bibtype C - Conference Paper (international conference)
ARLID 0314025
utime 20240103190609.3
mtime 20081107235959.9
title (primary) (eng) Data Assimilation of Model Predictions of Long-Time Evolution of CS-137 Deposition on Terrain
specification
page_count 4 s.
media_type neni
serial
ARLID cav_un_epca*0314120
ISBN N
title Proceeding of the IEEE International Geoscience & Remote Sensing Symposium 2008
page_num 1-4
publisher
place Boston
name IEEE
year 2008
title (cze) Asimilace modelu dlouhodobého časového vývoje depozice Cs-137 na terénu
keyword data assimilation
keyword marginalized particle filter
keyword estimation
keyword covariance structure
author (primary)
ARLID cav_un_auth*0228606
name1 Hofman
name2 Radek
institution UTIA-B
full_dept Department of Adaptive Systems
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101176
name1 Pecha
name2 Petr
institution UTIA-B
full_dept Department of Adaptive Systems
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url 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
cas_special
project
project_id GA102/07/1596
agency GA ČR
country CZ
ARLID cav_un_auth*0227611
research CEZ:AV0Z10750506
abstract (eng) 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
abstract (cze) Článek presentuje schéma pro odhad spatio-temporálního vývoje kvantity s neznámým chybovým modelem založeným na LU modelu.
action
ARLID cav_un_auth*0243487
name IEEE International Geoscience & Remote Sensing Symposium 2008
place Boston
dates 06.07.2008-11.07.2008
country US
reportyear 2009
RIV DI
permalink http://hdl.handle.net/11104/0164665
arlyear 2008
mrcbU63 cav_un_epca*0314120 Proceeding of the IEEE International Geoscience & Remote Sensing Symposium 2008 N 1 4 Boston IEEE 2008