1 publication

• Published Subscription 24 Jul 2025

  Enhancing Demand Forecasting in Supply Chains Through Deep Learning Techniques

  By Mohamed Safar Niyas S, Sipisuhav G, Rubesh K K, Ms.Akila K

  Abstract: Demand forecasting is critical in supply chain management, particularly for perishable goods, where inaccurate predictions can lead to significant financial losses and wastage. This paper explores the application of advanced deep learning techniques for food demand forecasting to optimize inventory management, reduce stockouts and overstock situations, and improve overall supply chain efficiency. By employing architectures such as LSTM, Bi-LSTM, Stacked-LSTM, and Transformer-based models, this research demonstrates the transformative potential of …

  Published in NOLEGEIN Journal of Management Information Systems · Vol. 8, Issue 2, 2025 · pp. 1–8 Read article →