Groundwater Level Forecasting Using Random Forest and Linear Regression Neural Network Models
—Predicting the groundwater level has recently
become very important research topic especially with the
rise of population density and consequently increasing the
water demand. This paper uses the Random Forest and
linear regression neural network models to predict the
groundwater level of Wadi-Alshaty district in the South
West part of Libya. The results are compared with that
obtained using the hydrologic long-term forecasting
graphical approach. One of the most important findings of
this study is the effectiveness of the neural network models
to investigate the fluctuation of the groundwater levels over
time (20 years)
Amna Elhawil, Alarabi Naji, Malak Nuesry, Almabruk Sanossi(12-2021)
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