2023 Vol.6 Jun. N0.3

• Title: Traffic demand forecasting method for urban railroad passenger hubs based on improved Tent mapping
• Name: Xiuli SUN
• Company: Shenzhen Metro Construction Group Co., Ltd,Shenzhen 518000,China
• Abstract:

  The current conventional traffic demand forecasting method mainly establishes the mathematical demand forecasting model by combining the time series method, which leads to the poor forecasting effect due to the lack of analysis of the traffic distribution characteristics of railroad passenger hubs. In this regard, an improved tent mapping-based traffic demand forecasting method for urban railroad passenger hubs is proposed. The tent mapping chaos mechanism is used to improve the Kbest function in the gravitational search algorithm, calculate the optimal adaptive weight coefficients, and analyze the traffic distribution characteristics of railway passenger hubs to construct a traffic trip distribution model. In the experiment, the proposed method is validated for prediction effect. The analysis of the experimental results shows that the algorithm converges well and has a more desirable prediction effect when the proposed method is used for traffic demand prediction.

  
  

• Keyword: tent mapping; urban railroad passenger transport; transportation hubs; prediction models.
• DOI: 10.12250/jpciams2023090509
• Citation form: Xiuli SUN.Traffic demand forecasting method for urban railroad passenger hubs based on improved Tent mapping [J]. Computer Informatization and Mechanical System,2023,Vol.6,pp.48-52

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