Publications by authors named "Binfan Lin"
Article Synopsis
- Short-cycle agricultural product sales forecasting helps reduce food waste by predicting demand accurately, matching supply with consumer needs.
- A hierarchical prediction model combining Random Forest (RF) and Extreme Gradient Boosting (XGBoost) is introduced to handle data volatility and improve prediction accuracy.
- Results show this model outperforms standalone RF and XGBoost, reducing prediction errors significantly and demonstrating effectiveness across various agricultural products, thereby optimizing supply chains and minimizing food waste.
