Improving Daily Reservoir Inflow Forecasts with Model Combination-Reference-Cited by-同舟云学术

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Improving Daily Reservoir Inflow Forecasts with Model Combination

Published:2005-03 Issue:2 Volume:10 Page:91-99
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Coulibaly Paulin¹²³²,Haché Mario¹²³²,Fortin Vincent¹²³²,Bobée Bernard¹²³²

Affiliation:

1. Dept. of Civil Engineering/School of Geography and Geology, McMaster Univ., Hamilton ON, Canada L8S 4L7 (corresponding author).

2. NSERC/Hydro-Québec Chair in Statistical Hydrology (INRS-ETE), Sainte-Foy PQ, Canada G1V 4C7.

3. Hydro-Québec Research Institute (IREQ), Varennes PQ, Canada J3X 1S1.

Publisher

American Society of Civil Engineers (ASCE)

Subject

General Environmental Science,Water Science and Technology,Civil and Structural Engineering,Environmental Chemistry

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%291084-0699%282005%2910%3A2%2891%29

Reference24 articles.

1. Multi-model data fusion for river flow forecasting: an evaluation of six alternative methods based on two contrasting catchments

2. The Combination of Forecasts

3. Daily reservoir inflow forecasting using artificial neural networks with stopped training approach

4. Some Statistical Results in the Combination of Forecasts

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