Modelling Bicycle Demand Using Autoregressive and Moving Average Models

3rd World Multidisciplinary Civil Engineering, Architecture, Urban Planning Symposium

土木建筑工程;文学

Starczewski, Jakub^1 ; Grzesica, Dariusz^1 ; Jirsa, Vojtech^2

Krakow University of Technology, Institute of Road and Railway Engineering, Department of Transportation Systems, 24 street, Warszawska

31155, Poland^1

University of Pardubice, Jan Perner Transport Faculty, Department of Transport Technology and Control, Studentská street 95, Pardubice

532 10, Czech Republic^2

关键词: Akaike information criterion;    ARMA model;    Autocorrelation analysis;    Autoregressive and moving average models;    Correlation coefficient;    Czech Republic;    Relative qualities;    Sustainable cities;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/471/6/062038/pdf
DOI  :  10.1088/1757-899X/471/6/062038

学科分类：土木及结构工程学

来源: IOP

【 摘 要 】

Bicycle transport is gaining importance in modern cities, therefore the modeling of its demand is most needed for sustainable city development. In this paper the measurement of number of bicyclists at one of the Czech Republic street was conducted. Monthly data in hourly periods was used. The autoregressive and moving average models of bicycle demand was calculated. Depending on ARMA parameters, to estimate the relative quality of statistical models, the Akaike Information Criterion (AIC) was used for a given set of data. In order to verify the correctness of the ARMA model, the residual autocorrelation analysis was carried out. The verification of the model's fit to the real data was made using the correlation coefficient.