Applicability of a nu-support vector regression model for the completion of missing data in hydrological time series

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F16%3A10328603" target="_blank" >RIV/00216208:11310/16:10328603 - isvavai.cz</a>
Result on the web
<a href="http://www.mdpi.com/2073-4441/8/12/560" target="_blank" >http://www.mdpi.com/2073-4441/8/12/560</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/w8120560" target="_blank" >10.3390/w8120560</a>

Result language
angličtina
Original language name
Applicability of a nu-support vector regression model for the completion of missing data in hydrological time series
Original language description
his paper analyzes the potential of a nu-SVR model to simulate water levels in a network of sensors in four nested experimental catchments in a mid-latitude montane environment. The model was applied to a range of typical runoff situations, including a single event storm, multi-peak flood event, snowmelt, rain on snow and a low flow period. The simulations based on daily values proved the high efficiency of the nu-SVR modeling approach to simulate the hydrological processes in a network of monitoring stations. The model proved its ability to reliably reconstruct and simulate typical runoff situations, including complex events, such as rain on snow or flooding from recurrent regional rain.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
DA - Hydrology and limnology
OECD FORD branch
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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