摘要
针对季节性时间序列,分别探讨了四种预测模型.以中国国内生产总值季度数据为研究对象,进行统计建模分析.结果表明,四种模型预测误差稍有差异,但总体上都具有较优的预测精度.最后对2021年我国国内生产总值四个季度数据进行了预测,为我国国内生产总值预测分析提供参考.在综合建模分析的基础上,着重培养学生统计建模思想和解决复杂问题的综合能力和高阶思维以及在真实情境中所激发的品格、价值观和使命感.
For seasonal time series,four forecasting models are discussed.Taking China's GDP as the research object,statistical modeling is carried out.The forecast errors of different models are compared.The results show that the prediction errors of the four models are slightly different,but in general they all have better prediction accuracy.Finally,the paper forecasts the four quarters of China’s GDP in 2021,which provides a reference for China’s GDP forecast and analysis.At the same time,on the basis of comprehensive modeling analysis,it focuses on cultivating students'statistical modeling thinking,and cultivating students'comprehensive ability and higher-order thinking in solving complex problems,as well as the character,values and sense of mission inspired in real situations.
作者
韩苗
周圣武
金子龙
HAN Miao;ZHOU Shengwu;JIN Zilong(School of Mathematics,China University of Mining and Technology,Xuzhou Jiangsu 221116,China)
出处
《大学数学》
2022年第6期53-60,共8页
College Mathematics
基金
高等学校大学数学教学研究与发展中心教学改革项目(CMC20210402)
江苏省高等教育教改研究立项课题(2019JSJG339)
国家自然科学基金(71871215)。
