스태킹 앙상블 모형을 활용한 치과 재고 수요예측 모델
Dental Inventory Demand Forecasting Model with Stacking Ensemble Models
- 주제(키워드) Dental Inventory , Stacking Ensemble Model , Demand Forecasting , Machine Learning
- 발행기관 한국SCM학회
- 발행년도 2023
- 총서유형 Journal
- KCI ID ART003011499
- 본문언어 한국어
초록/요약
In the context of businesses, securing competitiveness through cost reduction and operational efficiency is essential, and the importance of inventory management continues to grow. To conduct efficient inventory management, accurate demand forecasting is crucial, and this applies not only to businesses but also to healthcare institutions such as hospitals. Currently, it is safe to say that South Korea possesses world-class dental technology. However, when it comes to demand forecasting for dental inventory, which is directly related to dental revenue, research in comparison to the global dental technology level is still in a less advanced state, with ample room for improvement. Therefore, this study aims to refine the model for predicting the demand for dental medical items and enhance the dental inventory management system based on it. To achieve this, we will analyze the characteristics of demand data for dental products and develop a stacking ensemble model that combines various prediction models. Ultimately, we intend to demonstrate that the demand forecasting performance is improved when using the stacking ensemble model compared to using a single prediction model, enabling more effective dental inventory management.
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