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Simulating flows in a measure profile using artificial intelligence methods
 Pavelková, Růžena ; BBA, Šárka Zemanová, (referee) ; Kozel, Tomáš (advisor)
The thesis examines the possibility of using artificial intelligence methods for simulating average daily flows in selected measure profiles. In the theoretical part the main factors of the rainfall-runoff process and the methods used in the practical part are described. The practical part of the thesis deals with the construction of two models. The first model predicts the flow for episodes emanating only from rain events, the second model additionally considers snow cover. Artificial intelligence methods, specifically neural networks, are used to build the model, which are created in the MATLAB working environment. The selected criteria were used to evaluate the outputs of the models. Finally, the limits of applicability of the developed models containing neural networks were determined. In general, acceptable results were achieved.
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See also: similar author names
4 Pavelková, Radka
6 Pavelková, Renata
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