基于灰色GM(1,1)-马尔科夫模型的职业病预测研究

为准确预测量化我国职业病的发病趋势，在灰色GM(1,1)模型的基础上结合马尔科夫过程构建灰色GM(1,1)-马尔科夫预测模型，探讨灰色GM(1,1)-马尔科夫模型在职业病预测领域的应用。通过平均相对误差、后验差比值、小误差概率3个指标对该组合模型的预测精度进行评估。结果表明:10维灰色GM(1,1)-马尔科夫模型与原始数列的拟合程度较高，预测精度等级为一级（好），该组合模型的预测精度优于单一的灰色GM(1,1)预测模型；在遵循新陈代谢原理的情况下，我国职业病发病呈现上升态势，2015—2018年的职业病发病例数依次为31 196，36 284，37 724，39 147例。

Study on prediction of occupational diseases based on grey GM(1,1)-Markov model

In order to predict the incidence trend of occupational diseases accurately, a grey GM(1,1)-Markov prediction model was established based on the grey GM(1,1) model combined with the Markov process, and the application of this model in the field of occupational diseases was discussed. The prediction accuracy of the combined model was evaluated by three indexes including the average relative error, the posterior error ratio and the small error probability. The results showed that the ten-dimensional grey GM(1,1)-Markov model had higher fitting degree with the original sequence, and the grade of prediction accuracy was the first grade (good). The prediction accuracy of the combined model was better than that of the single grey GM(1,1) prediction model. In accordance with the metabolic principle, the incidence of occupational diseases in China presented a rising trend, and the incidence cases numbers of occupational diseases from 2015 to 2018 were 31196, 36284, 37724 and 39147 respectively.