计算机与现代化Issue(9)：46-49,4.DOI:10.3969/j.issn.1006-2475.2015.09.010
Hilbert-Huang变换在民航客运量预测中的算法研究
Algorithm of Hilbert-Huang Transform in Forecast of Passenger and Freight Volume
摘要
Abstract
In order to improve the prediction accuracy of non-stationary time series, the paper used Empirical Mode Decomposi-tion( EMD) method of Hilbert-Huang transform theory to decompose non-stationary time series into several IMF components of single frequency. Using the neural network model to predict IMF, the prediction results are reconstructed and weighted. The ac-curacy of prediction will be improved. It can also predict the transport volume in a certain period of time on the basis of the histor-ical passenger data. The experimental results show that the improved algorithm is better than the neural network method, etc.关键词
Hilbert-Huang变换/预测精度/经验模态分解/时间序列/神经网络Key words
Hilbert-Huang transform/prediction accuracy/Empirical Mode Decomposition(EMO)/time series/neural network分类
交通工程引用本文复制引用
潘卫军,潘月晓,卢国盼,曾琛..Hilbert-Huang变换在民航客运量预测中的算法研究[J].计算机与现代化,2015,(9):46-49,4.基金项目
国家自然科学基金委员会与中国民用航空局联合资助项目( U1433126) （ U1433126）
中国民航局科技资助项目(MHRD20130213) （MHRD20130213）
民航安全能力建设基金资助项目(XN2013003) （XN2013003）
