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Application of neural approaches to one-step daily flow forecasting in Portuguese watersheds
Institution:1. Departamento Ciencias Agroforestales, EPS, Campus Universitario de La Rábida, Universidad de Huelva, 21819 Palos de la Frontera, Huelva, Spain;2. Departamento Engenharia Civil, SHRH, Instituto Superior Técnico (IST), Avda. Rovisco Pais, 1049-001 Lisboa, Portugal;1. Department of Civil Engineering, McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4K1, Canada;2. School of Geography and Earth Sciences McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4K1, Canada;3. Institut de Recherche d’Hydro-Québec (IREQ), 1800, Lionel-Boulet, Varennes, Québec J3X 1S1, Canada;4. BC Hydro, Hydrology, 6911 Southpoint Drive, Burnaby, British Columbia V3N 4X8, Canada;5. National Hydrology Research Centre, Meteorological Service of Canada, 11 Innovation Blvd, Saskatoon, Saskatchewan S7N 3H5, Canada;1. College of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China;2. Henan Key Lab of Information-based Electrical Appliances, Zhengzhou University of Light Industry, Zhengzhou 450002, China;1. Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia, Vancouver, BC, Canada;2. Climate Data and Analysis Section, Climate Research Division, Environment and Climate Change Canada, Canada;1. School of Marine Sciences, Sun Yat-sen University, Guangzhou 510275, China;2. Guangdong Research Institute of Water Resources and Hydropower, Guangdong Provincial Key Laboratory of Hydrodynamics, Guangzhou 510630, China;3. State-province Joint Engineering Laboratory of Estuarine Hydraulic Technology, Guangzhou 510275, China;4. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China
Abstract:
Keywords:
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