Počet záznamů: 1
Marginalized Particle Filtering Framework for Tuning of Ensemble Filters
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SYSNO ASEP 0367533 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Marginalized Particle Filtering Framework for Tuning of Ensemble Filters Tvůrce(i) Šmídl, Václav (UTIA-B) RID, ORCID
Hofman, Radek (UTIA-B) RIDZdroj.dok. Monthly Weather Review - ISSN 0027-0644
Roč. 139, č. 11 (2011), s. 3589-3599Poč.str. 10 s. Jazyk dok. eng - angličtina Země vyd. US - Spojené státy americké Klíč. slova ensemble finter ; marginalized particle filter ; data assimilation Vědní obor RIV BB - Aplikovaná statistika, operační výzkum CEP VG20102013018 GA MV - Ministerstvo vnitra GP102/08/P250 GA ČR - Grantová agentura ČR CEZ AV0Z10750506 - UTIA-B (2005-2011) UT WOS 000296475700014 EID SCOPUS 84855783419 DOI 10.1175/2011MWR3586.1 Anotace Marginalized particle ltering (MPF), also known as Rao-Blackwellized particle filtering has been recently developed as a hybrid method combining analytical lters with particle filters. In this paper, we investigate the prospects of this approach in enviromental modelling where the key concerns are nonlinearity, high-dimensionality, and computational cost. In our formulation, exact marginalization in the MPF is replaced by approximate marginalization yielding a framework for creation of new hybrid lters. In particular, we propose to use the MPF framework for on-line tuning of nuisance parameters of ensemble filters. Strength of the framework is demonstrated on the joint estimation of the inflation factor, the measurement error variance and the length-scale parameter of covariance localization. It is shown that accurate estimation can be achieved with a moderate number of particles. Moreover, this result was achieved with naively chosen proposal densities leaving space for further improvements. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2012
Počet záznamů: 1