Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm

Atmospheric Research

Volumn 197, Issue , 2017, Pages 42-63

  Prasad, Ramendra ^a   Deo, Ravinesh C ^a   Li, Yan ^a   Maraseni, Tek ^a  

^a UNIVERSITY OF SOUTHERN QUEENSLAND   (Australia)

Author keywords

Drought in Murray Darling Basin; Iterative input selection algorithm, MODWT; Streamflow forecasting; Wavelet hybrid model

Indexed keywords

DISCRETE WAVELET TRANSFORMS; DROUGHT; ERRORS; FORECASTING; FORESTRY; ITERATIVE METHODS; MATRIX ALGEBRA; METEOROLOGY; NEURAL NETWORKS; OPTIMIZATION; STREAM FLOW; WATER LEVELS; WATER RESOURCES; WAVELET TRANSFORMS;

HYBRID ARTIFICIAL NEURAL NETWORK; HYBRID MODEL; INPUT SELECTION; MAXIMUM AND MINIMUM TEMPERATURES; MAXIMUM OVERLAP DISCRETE WAVELET TRANSFORMS; MURRAY-DARLING BASIN; PERFORMANCE OPTIMIZATIONS; STREAMFLOW FORECASTING;

TREES (MATHEMATICS);

ALGORITHM; ARTIFICIAL NEURAL NETWORK; DROUGHT; FORECASTING METHOD; HYDROLOGICAL MODELING; OPTIMIZATION; PRECISION; STREAMFLOW; WATER LEVEL; WATER RESOURCE; WAVELET ANALYSIS;

AUSTRALIA; DARLING RIVER; GWYDIR RIVER; MURRAY-DARLING BASIN; NEW SOUTH WALES; RICHMOND RIVER;

EID: 85021292297     PISSN: 01698095     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.atmosres.2017.06.014     Document Type: Article

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