River Flow Modeling in Semi-Arid and Humid Regions Using an Integrated Method Based on LARS-WG and LSTM Models
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DOI: 10.1007/s11269-023-03527-8
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- Khabat Khosravi & Ali Golkarian & John P. Tiefenbacher, 2022. "Using Optimized Deep Learning to Predict Daily Streamflow: A Comparison to Common Machine Learning Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(2), pages 699-716, January.
- Esmaeil Silakhori & Mohammad Reza Dahmardeh Ghaleno & Sarita Gajbhiye Meshram & Ehsan Alvandi, 2022. "To assess the impacts of climate change on runoff in Golestan Province, Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(1), pages 281-300, May.
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Keywords
Deep learning method; LARS-WG; Runoff; Semi-arid region; Temperature;All these keywords.
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