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What is Hybrid Inventory Forecasting Models about?

The document outlines various papers focused on hybrid forecasting methods for inventory management in e-commerce and retail, highlighting methodologies such as LSTM, ARIMA, and machine learning models like XGBoost and CatBoost. Key findings indicate that hybrid models significantly outperform traditional methods, with XGBoost excelling in short-term forecasts and CatBoost in long-term forecasts. The integration of advanced techniques like Graph Neural Networks enhances accuracy by capturing complex custome

Author

mrted6000

Language

EN