A self-tuning ANN model for simulation and forecasting of surface flows
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DOI: 10.1007/s11269-016-1301-2
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- Omid Bozorg-Haddad & Pouria Yari & Mohammad Delpasand & Xuefeng Chu, 2022. "Reservoir operation under influence of the joint uncertainty of inflow and evaporation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(2), pages 2914-2940, February.
- Wen-Ping Tsai & Yen-Ming Chiang & Jun-Lin Huang & Fi-John Chang, 2016. "Exploring the Mechanism of Surface and Ground Water through Data-Driven Techniques with Sensitivity Analysis for Water Resources Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4789-4806, October.
- Mehdi Kazemi & Omid Bozorg-Haddad & Elahe Fallah-Mehdipour & Xuefeng Chu, 2022. "Optimal water resources allocation in transboundary river basins according to hydropolitical consideration," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(1), pages 1188-1206, January.
- Ali Ahani & Mojtaba Shourian & Peiman Rahimi Rad, 2018. "Performance Assessment of the Linear, Nonlinear and Nonparametric Data Driven Models in River Flow Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(2), pages 383-399, January.
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Keywords
Artificial neural network; Runoff parameters; Simulation and forecasting; Effective factors; Optimization; Genetic algorithm;All these keywords.
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