Abstract
It is crucial to the economic and social development of the entire city to accurately predict its traffic passenger volume. For Sanya, as a coastal tourism city, it is rather vital to analyse the traffic volume to its tourism development. This paper, based on the tourism statistical data of monthly passenger volume from 2012 to 2017 in Sanya, applied ARIMA prediction model and grey Markov model to fit and predict the passenger volume. Upon empirical analysis, the result indicates that the mean absolute percentage error (MAPE) of such two models is 4.42% and 3.78% respectively with high prediction precision. Finally, the grey Markov model was utilized for trend extrapolation prediction and it has been found that the passenger volume in 2018 in Sanya would be expected to reach almost 36 million. Such prediction result would play an active role in policy formulation in the tourism and transportation industries, etc. in Sanya City.
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Acknowledgements
This research was financially supported by Hainan Provincial Natural Science Foundation of China (618QN258). Thanks to Professor PhD Zhao Qiu and Professor Ming-rui Chen, as correspondents of this paper.
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Liu, X., Wan, F., Chen, L., Qiu, Z., Chen, Mr. (2018). Research on Traffic Passenger Volume Prediction of Sanya City Based on ARIMA and Grey Markov Models. In: Zhou, Q., Miao, Q., Wang, H., Xie, W., Wang, Y., Lu, Z. (eds) Data Science. ICPCSEE 2018. Communications in Computer and Information Science, vol 902. Springer, Singapore. https://doi.org/10.1007/978-981-13-2206-8_28
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DOI: https://doi.org/10.1007/978-981-13-2206-8_28
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