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

Water (Switzerland)

Volumn 8, Issue 12, 2016, Pages

  Langhammer, Jakub ^a   Česák, Julius ^a  

^a CHARLES UNIVERSITY   (Czech Republic)

Author keywords

Data driven model; Precipitation; Runoff; Sensor network; Snowmelt; SVR

Indexed keywords

CATCHMENTS; FLOODS; PRECIPITATION (CHEMICAL); RAIN; REGRESSION ANALYSIS; RUNOFF; SENSOR NETWORKS; SNOW; SNOW MELTING SYSTEMS; TIME SERIES; WATER LEVELS;

DATA-DRIVEN MODEL; EXPERIMENTAL CATCHMENTS; EXPERIMENTAL RESEARCH; HYDROLOGICAL PROCESS; HYDROLOGICAL TIME-SERIES; SNOWMELT; SUPPORT VECTOR REGRESSION (SVR); SUPPORT VECTOR REGRESSION MODELS;

COMPLEX NETWORKS;

CATCHMENT; DATA ACQUISITION; FLOOD; FLOODING; HYDROLOGICAL MODELING; LOW FLOW; NUMERICAL MODEL; PEAK FLOW; PRECIPITATION (CLIMATOLOGY); RECONSTRUCTION; RUNOFF; SNOWMELT; SUPPORT VECTOR MACHINE; TIME SERIES ANALYSIS;

EID: 85002907353     PISSN: None     EISSN: 20734441     Source Type: Journal    
DOI: 10.3390/w8120560     Document Type: Article

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