摘要
针对城际铁路车站客流预测问题,文章采用离散小波分析方法对城际铁路车站原始日客流量数据进行小波分解;对分解得到的各层小波系数,利用AIC赤池信息准则进行ARIMA建模;利用训练得到的ARIMA模型进行预测未来一段时间客流数据的高频分量和低频分量,并对其进行小波重构,从而得到未来一段时间的预测客流数据;最后以广珠城际铁路某车站实际客流数据为例,对文章所提出的客流预测模型和客流预测算法进行了验证。实验结果表明,文章所提方法客流预测方法具有一定的预测精度。
In order to solve the problem of passenger flow prediction in intercity railway stations,this paper uses discrete wavelet analysis methods to decompose the original daily passenger flow data of intercity railway stations.For each layer of the wavelet coefficients obtained by decomposition,ARIMA modeling is carried out by using AIC Chichi information standard.The ARIMA model is used to predict the high frequency and low frequency components of passenger flow data for a certain period of time,and the wavelet reconstruction is performed to obtain the predicted passenger flow data for a certain period of time.Finally,taking the actual passenger flow data of a station of the Guangzhou-Zhuhai Intercity Railway as an example,the passenger flow prediction model and passenger flow prediction algorithm proposed in this paper are validated.The experimental results show that the passenger flow prediction method proposed in this paper has a certain degree of prediction accuracy.
作者
施玉欣
陈凌燕
梁颖怡
陈可欣
李锡钦
Shi Yuxin;Chen Lingyan;Liang Yingyi;Chen Kexin;Li Xiqin(School of Rail Transit Wuyi University,Jiangmen 529020,China)
出处
《江苏科技信息》
2019年第29期30-34,共5页
Jiangsu Science and Technology Information
基金
国家级大学生创新训练项目
项目编号：201811349036
关键词
城际铁路
客流预测
小波分析
ARIMA模型
intercity railway
passenger flow prediction
wavelet analysis
ARIMA model
作者简介
施玉欣(1996—),女,广东江门人,本科生,研究方向:城际铁路车站客流预测方法。
