A new approach to the prediction of passenger flow in a transit system

被引：34

作者：

Zhao, Shu-Zhi ^{[1
]}

Ni, Tong-He ^{[1
]}

Wang, Yang ^{[1
]}

Gao, Xiang-Tao ^{[1
]}

机构：

[1] Jilin Univ, Transportat & Traff Coll, Changchun 130025, Peoples R China

来源：

COMPUTERS & MATHEMATICS WITH APPLICATIONS | 2011年 / 61卷 / 08期

关键词：

Bus passenger flow; Non-linear prediction; Chaos recognition; Wavelets; MODEL; CHAOS;

D O I：

10.1016/j.camwa.2010.08.023

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A non-linear model is proposed for predicting the rate of passenger flow in a transit system, and its chaotic characteristic is observed. Using wavelets analysis, the passenger flow data for a whole day are decomposed in a multi-scale way to obtain decomposition sequences. Subsequently, a neural network approach is used to predict the sequences. Finally the passenger flow value can be predicted when the predicted sequences are reconstructed. Results show that the present approach is a feasible method for passenger flow prediction. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：1968 / 1974

页数：7

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