Deep Learning for Multi-Source Data-Driven Crop Yield Prediction in Northeast China
Jian Lu,
Jian Li,
Hongkun Fu
et al.
Abstract:The accurate prediction of crop yields is crucial for enhancing agricultural efficiency and ensuring food security. This study assesses the performance of the CNN-LSTM-Attention model in predicting the yields of maize, rice, and soybeans in Northeast China and compares its effectiveness with traditional models such as RF, XGBoost, and CNN. Utilizing multi-source data from 2014 to 2020, which include vegetation indices, environmental variables, and photosynthetically active parameters, our research examines the… Show more
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