Ashraf ALDabbas

Deep learning prediction of multi-depth soil temperature using climatic variables in eastern Hungary

Three predictive approaches were applied: linear regression, random forest, and a deep neural network to predict soil temperature at depths of 5 and 50 cm in Central Europe, specifically eastern Hungary, highlighting soil temperature as a sensitive indicator of environmental change and demonstrating the value of deep l...