Open AccessDrugs Sale Forecasting Based on SVR Integrated Promotion Factors
Author(s) -
Yang Liu,
Xiao Yang,
Cheng Zhu,
Jie Meng
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1910/1/012056
Subject(s) - promotion (chess) , order (exchange) , sales promotion , sales forecasting , business , computer science , sales management , machine learning , marketing , operations research , finance , mathematics , politics , political science , law
In order to improve the inventory management level of pharmaceutical chain enterprise, drug sales forecasting is needed. Using machine learning SVR model, we forecast the drugs sale amount with a relatively high accuracy. Suppose the sales amount is influenced by promotion strategy, we integrated the promotion factors into the SVR model. Experimental result of drug sales prediction on the real sales data of a large chain drug company S shows that the SVR algorithm integrated with promotion factors get the accuracy rate of 91% and the algorithm can greatly improve the drug sales prediction results compared with traditional time series model.