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National Repository of Grey Literature

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Hybrid Method for Modelling and State Estimation of Dynamic Systems Brablc, Martin ; Blaha, Petr (referee) ; Bugeja, Marvin (referee) ; Grepl, Robert (advisor) Tato Disertační práce se zabývá vývojem nové hybridní metody pro současné odha- dování stavů a parametrů nelineárních dynamických systémů, založené na myšlence lokálních lineárních modelů, která využívá odhad nejistoty parametrů modelu pro automatické nastavení některých parametrů Kalmanova filtru (KF), čímž se výrazně zjednodušuje její nasazení a nastavení v praktických aplikacích. V první části se disertační práce věnuje shrnutí aktuálního stavu poznání v oblasti dynamických systémů, simultánní estimace, KF a modelování nelineárních dynamických systémů. Následně se ve dvou samostatných kapitolách věnuje modifikaci KF pro situace, kde dominantním vlivem způsobujícím procesní šum jsou nepřesné parametry modelu, a dále modifikaci metody Receptive field weighted regression (RFWR) tak, aby mohla být použita pro duální estimaci. Nakonec práce popisuje vyvinutou hybridní metodu složenou z modifikovaných algoritmů RFWR a KF nazvanou Receptive field dual estimation - (RFDE) a demonstruje její funkčnost na simulačních i reálných datech. Detailed record

Forest Soil Physico-Chemical Sorption Spatial Links in Central-European Systems of Site Geographical Divisions Samec, Pavel ; Balková, M. ; Kučera, A. Spatial links among soil property values influence variability of soil sorption. The aim of this study was to compare the effect of geotectonic, soil-and biogeographical divisions on forest soil physicochemical sorption spatial links. The effect was investigated through optimal model selection and its comparison among the soil cover division systems of Central-European Highlands in the Czech Republic. Optimal model was selected through the closest-fitting estimations of linear global and local regressions between sorption and chemical or geomorphological forest soil properties. The optimal model comparison was carried out through linear regression with bedrock type proportion (geodiversity) at units of particular division systems. Chemical properties influenced forest soil sorption more than relief. Soil base saturation (BS) was locally more divided than cation exchange capacity (CEC). Local regression of BS with Al2O3 was divided by geotectonic systems the most, but it was not influenced by geodiversity. Geodiversity influenced local regression of CEC with Al2O3 in soil regions as well as regression with C/N in biogeographical regions. Differences between spatial links of BS and CEC suggest that forest soil sorption is divided into multi-level clusters. Spatial link modelling of soil sorption can optimalize forest growth condition division for effective management use. Detailed record

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