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| Study on the application of linear regression-grey model(1，1) coupling model in the prediction of regional health human resource |
| Cao Yuanyuan |
| Department of Anesthesiology, Shaoxing Central Hospital, Shaoxing 312000, China |
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Abstract Objective Taking the number of doctors per thousand for prediction, this paper discussed the application of grey model GM(1，1)-linear regression coupling model in the prediction of Shaoxing regional medical human resources, so as to provide methodology reference for forecasting health personnel．MethodsThe grey model (1，1) was built up with Excel formula to predict per capita GDP. The predictive value was substituted into the regression equation for the annual prediction of Shaoxing regional nursing human resource．Results The fitting error between predicted value and actual value was small when using the grey model GM(1,1)-linear regression coupling model in the prediction of regional nursing human resource. The accuracy level of this coupling model prediction was excellent, the predicted number of doctors per thousand population in 2018 and 2019 was 3.18 and 3.38 respectively, and the prediction result could be used as a reference for the target year (C=0.104 3，P=1). Conclusion The coupling model not only remedied the defect that grey system model did not include 1inear factors, but also improved the fact that linear forecasting model could not express exponential growth．This model can be used to predict health human resources.
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Received: 13 September 2018
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