基于小波变换的组合预测模型在南京市GDP预测中的应用  

The Application of Combined Forecast Model Base on Wavelets on the Predict of Nanjing’s GDP

作　　者：张敏[1] 党耀国[2] ZHANG Min;DANG Yao-guo(Jincheng College, Nanjing University of Aeronautics and Astronautics, Nanjing 211156, China;College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211100 China)

机构地区：[1]南京航空航天大学金城学院,江苏南京211156 [2]南京航空航天大学经济与管理学院,江苏南京211106

出　　处：《数学的实践与认识》2018年第7期111-118,共8页Mathematics in Practice and Theory

基　　金：江苏高校哲学社会科学研究项目(2016SJD790058);江苏省社会科学基金重点项目(15GLA001)

摘　　要：随着南京经济的快速发展，产业结构逐步优化，南京市三次产业未来发展趋势如何？对南京市2000-2015年的GDP数值进行小波变换，对变换后的高频信息用AR模型进行预测，对低频信息用新陈代谢GM（1，1）模型进行预测，两种预测结果组合后可知“十三五”期间南京市GDP及三次产业产值．结果表明，组合模型预测精度更高．在对计算结果进行分析的基础上，科学探讨产业结构转型的路径与对策，旨在给决策部门提供参考．With the rapid development of Nanjing economy and the gradual optimization of industrial structure, how is the development trend of the three industries in Nanjing？ In this paper, the GDP value of Nanjing from 2000 to 2015 is decomposed by frequency information is used to predict by the AR model while the low frequency information is used to forecast by the CM（1,1） model. The two predictions are combined to get the data of Nanjing＇s GDP and three industrial output value during the period of the ＂13th Five-Year Plan＂. The results show that the combined model prediction accuracy is higher. According to the calculation results, analyzing the path and countermeasures of the industrial structure transformation, aims to provide reference for decision-making departments.

关 键 词：小波变换 AR模型 新陈代谢GM(1 1)模型 GDP预测 

分 类 号：F127[经济管理—世界经济]