Number of the records: 1

Neural and Fuzzy Modelling of Hydrological Data

SYSNO ASEP	0425662
Document Type	V - Research Report
R&D Document Type	The record was not marked in the RIV
Title	Neural and Fuzzy Modelling of Hydrological Data
Author(s)	Neruda, Roman (UIVT-O)_{SAI, RID, ORCID} Coufal, David (UIVT-O)_{RID, SAI, ORCID}
Issue data	Prague: ICS AS CR, 2012
Series	Technical Report
Series number	V-1172
Number of pages	51 s.
Language	eng - English
Country	CZ - Czech Republic
Keywords	environmental modelling ; fuzzy systems ; neural networks ; meta-learning
Subject RIV	IN - Informatics, Computer Science
R&D Projects	OC10047 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
Institutional support	UIVT-O - RVO:67985807
Annotation	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.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2014

Number of the records: 1