Abstract
This paper presents a study based on passenger hailing safety big data collection and PASW statistical analysis. A regression analysis model was used on data collected to study whether two or more variables were correlated. Changes in the direction and strength of correlation, and a regression analysis of arguments given estimates for the conditional expectation of the dependent variables, fully revealed the complex dependence. In addition, the RSS, which reflects the influence of random errors on dependent variables, measured the influence of the variance of factors other than passengers’ hailing safety, data collection, and statistics analysis. In the linear regression analysis model, to improve traffic safety prediction and control, R2 represents the contribution rate of analytic variables to a forecast change.
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Meng, S.H., Huang, A.C., Huang, T.J., Chen, J., Pan, J.S. (2017). Passenger Hailing Safety PASW Modeler and Big Data Statistical Analysis Study. In: Pan, JS., Snášel, V., Sung, TW., Wang, X. (eds) Intelligent Data Analysis and Applications. ECC 2016. Advances in Intelligent Systems and Computing, vol 535. Springer, Cham. https://doi.org/10.1007/978-3-319-48499-0_2
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DOI: https://doi.org/10.1007/978-3-319-48499-0_2
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