Národní úložiště šedé literatury Nalezeno 4 záznamů.  Hledání trvalo 0.01 vteřin. 
Neural and Fuzzy Modelling of Hydrological Data
Neruda, Roman ; Coufal, David
The main goal of this work is to model flood waves based on runoff and precipitation data. We utilize data from the Smeda rivera catchment provided by the CHMI in order to build several models of flood episodes. Multilayer perceptron networks and Fuzzy system models are used and their performance is compared to traditional hydrological approaches.
Plný tet: v1172-12 - Stáhnout plný textPDF
Plný text: content.csg - Stáhnout plný textPDF
Fixed and Variable-Width Gaussian Networks
Kůrková, Věra ; Kainen, P.C.
Plný tet: v1174-12 - Stáhnout plný textPDF
Plný text: content.csg - Stáhnout plný textPDF
Accuracy Estimates for Surrogate Solutions of Integral Equations by Neural Networks
Kůrková, Věra
Surrogate solutions of integral equations by neural networks are investigated theoretically. Upper bounds on speed of convergence of approximate solutions computable by neural networks with increasing model complexity to exact solutions described by Fredholm theorem are derived.

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