基于Elman神经网络的我国卫生总费用预测研究

Study on the Prediction of Total Health Expenditure in China Based on Elman Neural Network

目的通过Elman神经网络的构建预测卫生总费用数据,分析经济社会新常态以来卫生总费用的变化趋势。方法参考经济社会新常态以前卫生总费用的分析方法,总结构建了Elman神经网络对卫生总费用进行预测,发现预测模型性能较好。结果进入"新常态"以来,2016—2020年我国卫生总费用和国内生产总值都将呈逐年递增趋势。卫生总费用将由2016年的45 832.49亿元上涨到2020年的60 295.96亿元,国内生产总值将由2016年的720 945.7亿元上涨到2020年的810 274.7亿元,卫生总费用相对与国内生产总值的比重将从2016年的6.36%上涨到2020年的7.45%。结论新常态以来我国卫生总费用增长速度较快,相对于国内生产总值增速惊人;基于经济社会新常态构建的Elman神经网络预测模型有较好的预测精度,适用性强。

Objective Through the construction of the Elman neural network to forecast the total expenditure data on health,and to analyze the change trend of the total health expenditure in the economic and social new normal. Method Doing reference on health total expenditure analysis method before the new normal economy and sociey,summarizing that the Elman neural network was constructed to estimate the total health expenses,and the prediction results was good. Result Since entering the＂new normal＂,China＇s total health expenditure and gross domestic product will increase year by year from 2016 to 2020. The total health expenditure will increase from 4 583.249 billion yuan in 2016 to 60 295.96 billion yuan in 2020. The gross domestic product will rise from 72 094.57 billion yuan in 2016 to 81027.47 billion yuan in 2020,and the proportion of total health expenditure relative to GDP will rise from 6.36% in 2016 to 7.45% in 2020. Conclusion The total health expenses in China since the new normal growth rate increases faster,and its growth rate is surprising compared with gross domestic product（GDP）. The prediction model of Elman neural network based on the new normal of economic and social development has good prediction accuracy and strong applicability.