Abstract
The city airport serves as a fundamental infrastructure for air transportation, with its development planning largely contingent upon the prognostication of future airport activities' busyness. Given the multifarious factors that influence passenger flow, such as population size, economic structure, industrial policy, geographical location, and comprehensive transportation, grey system has the characteristic of incomplete information, and the passenger traffic at the airport conforms to this feature. In this article, the GM(1,1) grey prediction model and the GM(2,1) grey prediction model are respectively applied to predict the passenger flow of Sanya Airport, and the suitability of each model is compared. The outcomes show that the GM(2,1) grey model outperforms the GM(1,1) grey model in relation to the average relative error rate, the single point maximum error, the mean square error of relative error, and the average relative accuracy.
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Project supported by the Education Department of Hainan Province, project number: Hnky2022ZD-25.
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Chen, Y., Li, Y. (2023). Comparison of Two Grey Models’ Applicability to the Prediction of Passenger Flow in Sanya Airport. In: Yu, Z., et al. Data Science. ICPCSEE 2023. Communications in Computer and Information Science, vol 1880. Springer, Singapore. https://doi.org/10.1007/978-981-99-5971-6_17
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DOI: https://doi.org/10.1007/978-981-99-5971-6_17
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