Original title: Neural and Fuzzy Modelling of Hydrological Data
Authors: Neruda, Roman ; Coufal, David
Document type: Research reports
Year: 2012
Language: eng
Series: Technical Report, volume: V-1172
Abstract: 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.
Keywords: environmental modelling; fuzzy systems; meta-learning; neural networks
Project no.: OC10047 (CEP)
Funding provider: GA MŠk
Rights: This work is protected under the Copyright Act No. 121/2000 Coll.

Institution: Institute of Computer Science AS ČR (web)
Original record: http://hdl.handle.net/11104/0231494

Permalink: http://www.nusl.cz/ntk/nusl-170497


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Research > Institutes ASCR > Institute of Computer Science
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