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• W3091506459 abstract "Accurate streamflow prediction is a fundamental task for integrated water resources management and flood risk mitigation. The purpose of this study is to forecast the water inflow to lake Como, (Italy) using different machine learning algorithms. The forecast is done for different days ranging from one day to three days. These models are evaluated by three statistical measures including Mean Absolute Error, Root Mean Squared Error, and the Nash-Sutcliffe Efficiency Coefficient. The experimental results show that Neural Network performs better for streamflow estimation with MAE and RMSE followed by Support Vector Regression and Random Forest." @default.
• W3091506459 created "2020-10-08" @default.
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• W3091506459 date "2020-01-01" @default.
• W3091506459 modified "2023-09-26" @default.
• W3091506459 title "Evaluation of Machine Learning Techniques for Inflow Prediction in Lake Como, Italy" @default.
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• W3091506459 doi "https://doi.org/10.1016/j.procs.2020.09.087" @default.
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