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This study assesses land suitability for Golden Tangerine and Paddy Rice in Bac Son District, Vietnam, using Random Forest and Artificial Neural Network models based on various environmental factors. The ANN model showed better suitability predictions for both crops, while the RF model had higher classification accuracy for Paddy Rice. The findings emphasize the importance of model selection in land suitability assessments and suggest further research into hybrid modeling approaches and the inclusion of soc

Author

Linh Nguyen

Language

EN