城市轨道交通分段客流预测方法研究

智能学习系统与应用(英文) Pub Date : 2013-11-12 DOI:10.4236/JILSA.2013.54026

Qian Li, Yong Qin, Zi-yang Wang, Z. Zhao, Minghui Zhan, Yu Liu, Zhiguo Li

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引用次数: 11

摘要

本文对分段客流的短期预测方法进行了研究，选择了结合分段客流本身特点的BP神经网络。通过案例研究，我们设计了三种不同的方案。利用Matlab实现了对北京地铁2号线分段客流的预测，并进行了对比分析。实证研究表明，将分段客流数据特征与BP神经网络相结合，具有较好的预测精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method

This paper studies the short-term prediction methods of sectional passenger flow, and selects BP neural network combined with the characteristics of sectional passenger flow itself. With a case study, we design three different schemes. We use Matlab to realize the prediction of the sectional passenger flow of the Beijing subway Line 2 and make comparative analysis. The empirical research shows that combining data characteristics of sectional passenger flow with the BP neural network have good prediction accuracy.

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来源期刊

智能学习系统与应用(英文)

自引率

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发文量

135