DOI: https://doi.org/10.15802/stp2013/19676

Passenger flows prediction in major transportation hubs

O. O. Ozerova

Abstract


Purpose. An effective organization of passenger traffic, due to the reliability prediction of traffic flow in passenger transport hubs. In order to determine the parameters of prospective passenger transport areas it is essential to analyze the impact of various factors and determine the most influential ones. Methodology. The article presents the method of paired linear correlation for a more influential factors on passengers in intercity and commuter and possible use in predicting the linear regression equations. Passenger transport vessel areas and branches of industry are interconnected and are in the ratio of passengers and production. Findings. It is found that the coefficient of correlation is in complex dependence on the duration of the period of retrospective analysis. Evaluation of reliability correlation coefficients and coefficients of predictive models led to the conclusion that the population gives the most accurate prediction of passenger flows, providing account of changes in Ukraine during the period of transformation. Originality. Equations of dependence on the impact of macroeconomic indicators were obtained and the evaluation of the reliability results was received. Practical value. The results of analysis and calculations will make short-term forecasting of traffic flow. 


Keywords


forecasting; commuter transportation; urban transport; gross domestic product; the dynamics of population change; the coefficient of correlation

References


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Cited-by:

1. Integrated predicting model for daily passenger volume of rail transit station based on neural network and Markov chain
Zhong-Sheng Xiao, Bao-Hua Mao, Tong Zhang
2018 IEEE 3rd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)  First page: 578  Year: 2018  
doi: 10.1109/ICCCBDA.2018.8386582



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