A Forecasting Analysis of Health Technicians Demand in Hainan Province based on Several Combination Forecasting Models
Abstract
Objective:Several combination models were used to forecast the demand for health technicians in Hainan Province in order to find the best combination of forecasting models and thus provide the relevant departments with a more scientific basis for their planning. Methods:First using ARIMA method, GM(1,1) method and trend extrapolation method to establish single forecasting models, and then based on single models, adopt equal weight method , reciprocal  errors method ,odds-matrix method and artificial neural networks method to establish four kinds of combination forecasting models, finally evaluate all the prediction models and select the best model to make a short -term forecasting. Results:The combined forecasting model generally has a lower forecasting error than the single forecasting model. The combined artificial neural network model has the lowest forecasting error and is the relatively optimal model for forecasting health technicians. It is predicted that the demand for health technicians in Hainan Province will increase steadily from 2021 to 2023. Conclusion:The demand for health technicians in Hainan Province is still high, and training efforts should be further strengthened to lay a solid foundation of health care for the construction of the Hainan Free Trade Port.
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