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What is Weather-Enhanced Demand Forecasting for Rossmann about?

This research paper presents a demand forecasting model for 1115 Rossmann stores in Europe, utilizing a multivariate dataset that includes weather variables to enhance accuracy. The proposed Gated Recurrent Unit (GRU) model, optimized through Grid Search, outperforms traditional Long Short Term Memory (LSTM) models in predicting sales demand. The findings aim to improve inventory management and financial performance in the retail sector by providing more reliable sales forecasts.

Author

susitvl2001

Language

EN