DOI: 10.18178/wcse.2024.06.021
On the ES-LSTM Forecasting Model for Optimizing Drug Inventory Management: A Preliminary Attempt
Abstract— This study introduces and evaluates the ES-LSTM, a forecasting model that integrates exponential smoothing with LSTM networks to optimize drug inventory management. The ES-LSTM model was tested against traditional LSTM models using pharmaceutical sales data, demonstrating superior accuracy in capturing both peak and regular demand patterns. The findings indicate that ES-LSTM could revolutionize inventory management in healthcare, making it a promising area for further investigation.
Index Terms— ES-LSTM, Drug Inventory Management, Exponential Smoothing
Kittikorn Sriwichai
Suranaree University of Technology, THAILAND
Janejira Laomala
Suranaree University of Technology, THAILAND
Sayan Kaennakham
Suranaree University of Technology, THAILAND
Cite: Kittikorn Sriwichai, Janejira Laomala, Sayan Kaennakham, "On the ES-LSTM Forecasting Model for Optimizing Drug Inventory Management: A Preliminary Attempt," 2024 The 14th International Workshop on Computer Science and Engineering (WCSE 2024), pp. 139-143, Phuket Island, Thailand, June 19-21, 2024.