基于小波分析的BP-SARIMA模型的CPI预测  

CPI Prediction of BP-SARIMA Model Based on Wavelet Analysis

作　　者：彭乃驰 党婷 Peng Naichi;Dang Ting(Department of Information Science and Technology,Tourism and Culture College of Yunnan University,Lijiang Yunnan 674199,China)

机构地区：[1]云南大学旅游文化学院信息科学与技术系

出　　处：《统计与决策》2018年第16期22-25,共4页Statistics & Decision

基　　金：云南省教育厅科学研究基金项目(2015Y507)

摘　　要：文章以云南为例,对同比月度CPI原始数据进行小波阈值去噪处理,对去噪后数据作BP神经网络预测,通过SARIMA模型修正预测残差,从而建立了小波分析的BP-SARIMA模型。实证结果表明：小波分析的BP-SARIMA模型相对于未经小波分析的BP-SARIMA模型及未经SARIMA残差修正的小波分析的BP模型有更高的预测精度。This paper takes Yunan Province as example to de-noise wavelet threshold of monthly CPI raw data and predict the de-noised data by BP neural network, and then the paper uses the SARIMA model to correct predicted residuals and establish wavelet analytic BP-SARIMA model. The empirical results show that prediction accuracy of the wavelet analytic BP-SARIMA model is higher than that of the BP-SARIMA model without being processed by wavelet analysis and the BP model without residual correction by the SARIMA.

关 键 词：小波分析 BP神经网络 SARIMA模型 CPI 

分 类 号：F224[经济管理—国民经济] F201