Application of grey model (1, 1)-linear regression coupling model in the prediction of regional nursing human resource
10.3760/cma.j.issn.1674-2907.2018.02.022
- VernacularTitle:灰色模型和线性回归耦合模型在区域护理人力资源预测中的应用
- Author:
Jianchao LIN
1
;
Baofa YU
;
Chunbaixue YANG
;
Le XU
Author Information
1. 312000,浙江省绍兴第二医院党政办
- Keywords:
Nursing administration research;
Grey model (1;
1);
Linear regression models;
Nursing human resource;
Forecasting
- From:
Chinese Journal of Modern Nursing
2018;24(2):217-220
- CountryChina
- Language:Chinese
-
Abstract:
Objective Taking the prediction of the number of nurses per thousand cases as an example, to discuss the application of grey model GM(1, 1)-linear regression Coupling Model in the prediction of regional nursing human resource, so as to provide methodology reference for health human resource prediction.Methods The grey model GM (1, 1) was built up by EXCEL formula to predict the influencing factors of the number of nurses per thousand people. The predictive value of the influencing factors were substituted into the regression equation for the annual prediction of 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 is excellent, and the prediction result can be used as a reference for target year. Conclusions The coupling model not only makes up for the lack of 1inear factors in the grey system model, but also improves the defect that exponential growth cannot be expressed in the linear regression prediction model, so the construction of the coupling model is reasonable and feasible.
