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What is Bayesian Deep Learning for Soil Erosion Prediction about?

This study presents the development and interpretation of Bayesian-optimized deep learning models to enhance soil erosion susceptibility prediction and management in Eastern India. Utilizing the Revised Universal Soil Loss Equation (RUSLE) and advanced deep learning techniques, the models achieved high accuracy in identifying erosion-prone areas, with the DNN model reaching an accuracy of 0.93. The integration of SHAP value analysis provides insights into the influential factors for erosion, aiding decision

Author

lacofe1194

Language

EN