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21.
Guangping Qie Zhenxing Zhang Elias Getahun Emily Allen Mamer 《Journal of the American Water Resources Association》2023,59(3):554-570
Reservoir outflow is an important variable for understanding hydrological processes and water resource management. Natural streamflow variation, in addition to the streamflow regulation provided by dams and reservoirs, can make streamflow difficult to understand and predict. This makes them a challenge to accurately simulate hydrologic processes at a daily scale. In this study, three Machine Learning (ML) algorithms, Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN), were examined and compared to model reservoir outflow. Past, current, and future hydrologic and meteorological data were used as model inputs, and the outflow of next day was used as prediction. Simulation results demonstrated that all three models can reasonably simulate reservoir outflow. For Carlyle Lake, the coefficient of determination and Nash–Sutcliffe efficiency were each close to one for the three models. The coefficient of determination, relative mean bias, and root mean square error indicated that the SVM performed better than the RF and ANN, but the SVM output displayed a larger relative mean bias than that from RF and ANN. For Lake Shelbyville, the ANN model performed better than RF and SVM when considering the coefficient of determination, Nash–Sutcliffe efficiency, relative mean bias, and root mean square error. The study results demonstrate that the three ML algorithms (RF, SVM, and ANN) are all promising tools for simulating reservoir outflow. Both the accuracy and efficacy of the three ML algorithms are considered to support practitioners in planning reservoir management. 相似文献
22.
Ali Hussien Leta Seyoum Hussen Ahmed Alemu Tadesse 《Journal of Material Cycles and Waste Management》2023,25(4):2417-2430
Journal of Material Cycles and Waste Management - Increasing waste production and its disposal into the environment without treatment and resource recovery is considered as a threat to the... 相似文献
23.
Hassen Bantamlak Leta Seyoum Hussen Ahmed Alemu Tadesse 《Journal of Material Cycles and Waste Management》2023,25(4):2350-2364
Journal of Material Cycles and Waste Management - This study aimed to determine the quantity and quality of source separated organic household solid waste (SSOHSW) generation in Addis Ababa,... 相似文献