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Improving maize yield prediction performance via a hybrid framework coupling an optimized crop model and deep learning
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DOI：10.1016/j.agsy.2026.104768.png)
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Abstract
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• Coupling crop model and deep learning improves yield prediction. • A-dfLSTM with autoregressive feedback reduces prediction error by 10.5%. • High-precision predictions (R2 > 0.9) achieved 1 month prior to harvest.
Keywords:
maize yield prediction
crop model
deep learning
a-dfLSTM
autoregressive feedback
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