Research on Relationships among Three Parameters in Short-term Traffic Flow Forecasting

被引：1
|
作者：
Xiao Xinping [1 ]
Hu Yichen [1 ]
Guo Huan [1 ]
机构：
[1] Wuhan Univ Technol, Coll Sci, Wuhan 430070, Peoples R China
来源：
MECHANICAL AND ELECTRONICS ENGINEERING III, PTS 1-5 | 2012年 / 130-134卷
关键词：
Traffic flow parameters; Statistical correlation analysis; Grey relational analysis; Binary linear regression model without the intercept; GM(0,3) model;
D O I：
10.4028/www.scientific.net/AMM.130-134.2072
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
This paper expects to get the real-time changes of traffic flow by researching the relationships among the three basic parameters flow, speed and occupancy. we firstly carries out the statistical correlation analysis and grey relational analysis to study the connection between the traffic flow parameters flow and speed, flow and occupancy to get a conclusion that there doesn't exist a significant linear relationship between neither of the comparisons, and the influence of speed on the flow is a little bigger than that of occupancy. Then we try to establish the binary linear regression model without the intercept and GM (0,3) model to do the data fitting, the final simulation results illustrate that the two methods has effects in some extent, also explain the complexity of traffic flow.
引用
收藏
页码：2072 / 2076
页数：5
相关论文
共 50 条
  • [21] An Ensemble Learning Short-term Traffic Flow Forecasting with Transient Traffic Regimes
    Zhu, Jiasong
    [J]. ADVANCED TRANSPORTATION, PTS 1 AND 2, 2011, 97-98 : 849 - 853
  • [22] A Gaussian maximum likelihood formulation for short-term forecasting of traffic flow
    Lin, WH
    [J]. 2001 IEEE INTELLIGENT TRANSPORTATION SYSTEMS - PROCEEDINGS, 2001, : 150 - 155
  • [23] Short-term traffic flow forecasting based on ARIMA-ANN
    Hong-qiong, Huang
    Tian-hao, Tang
    [J]. 2007 IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1-7, 2007, : 480 - 483
  • [24] A Data Grouping CNN Algorithm for Short-Term Traffic Flow Forecasting
    Yu, Donghai
    Liu, Yang
    Yu, Xiaohui
    [J]. WEB TECHNOLOGIES AND APPLICATIONS, PT I, 2016, 9931 : 92 - 103
  • [25] Forecasting Model of Short-term Traffic Flow Based on Cloud Model
    Liu, Qin
    Xu, Jianmin
    [J]. ADVANCES IN STRUCTURAL ENGINEERING, PTS 1-3, 2011, 94-96 : 38 - 42
  • [26] SHORT-TERM TRAFFIC FLOW FORECASTING MODELS AND COMBINATORIAL OPTIMIZATION ALGORITHM
    Chen Song
    Zhang Min
    Peng De-wei
    [J]. DCABES 2009: THE 8TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND APPLICATIONS TO BUSINESS, ENGINEERING AND SCIENCE, PROCEEDINGS, 2009, : 394 - 397
  • [27] Short-term Traffic Flow Forecasting Based on Clustering and Feature Selection
    Sun, Zhanquan
    Wang, Yinglong
    Pan, Jingshan
    [J]. 2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8, 2008, : 577 - 583
  • [28] New Bayesian combination method for short-term traffic flow forecasting
    Wang, Jian
    Deng, Wei
    Guo, Yuntao
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2014, 43 : 79 - 94
  • [29] The study of short-term traffic flow forecasting based on theory of chaos
    Wang, J
    Shi, QX
    Lu, HP
    [J]. 2005 IEEE Intelligent Vehicles Symposium Proceedings, 2005, : 869 - 874
  • [30] Kernel Regression with a Mahalanobis Metric for Short-Term Traffic Flow Forecasting
    Sun, Shiliang
    Chen, Qiaona
    [J]. INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2008, 2008, 5326 : 9 - 16
12345