A Grey Polynomial Model Based Forecast and Analysis of Air Transport Turnover
Authors: 
Yuanying Wang, Jue LiuAuthors Info & Claims
Pages 539 - 543
Abstract
As one of the vital industries of economic and social development in China, the civil aviation industry has a fundamental role in the field of transportation. While accurate forecasting of the air transport turnover provide effective advice for Civil Aviation Industry's policy makers. Ttherefore, through analyzing characteristics of air transport turnover data, this paper establishes a grey polynomial model (GMP (1,1, N) ) so as to forecast the annual data of the total civil aviation transport turnover from 2011 to 2018 and the data of the total civil aviation transport turnover from January to May in 2023. Also it analyzes the development situation of Chinese aerial transportation, which could provide a reliable reference value for the depth improve and optimal management of air transportation
References
[1]
Civil Aviation Administration of China. 2020. Statistical Bulletin on the Development of the Civil Aviation Industry in 2019. http://www.caac.gov.cn/XXGK/XXGK/TJSJ/202006/t20200605_202977.html
[2]
Li, M. J., Zhou, Y., Shi, Y. Y. 2011. Turnover of Passenger Traffic Prediction for Civil Aviation Based on GM (1,1) Model. Journal of Civil Aviation Flight University of China. 22 (5): 29-31. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C44YLTlOAiTRKgchrJ08w1e7tvjWANqNvp8_V0HZwBnO6UdQXyqodEegt0lkZLBaRpS9kOqSllt5lG5duYHjBXke&uniplatform=NZKPT&src=copy
[3]
Liu, M. J., Tian, Y. N., Zhang, L., Jin, B. 2022. Application of Prophet-ARIMA Combined Model in Forecast of Civil Aviation Turnover. Computer Technology and Development. 32 (02): 148-153+160. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C44YLTlOAiTRKibYlV5Vjs7iJTKGjg9uTdeTsOI_ra5_XWtPO6KuPDQ5kfR4Jyn0VgP2qHNouCzd2bLbxWVNoZi4&uniplatform=NZKPT&src=copy
[4]
Luo, Y. C., Xu, Y. N., Deng, X. M. 2023. Forecasting of the total monthly transportation turnover of civil aviation based on ARIMA and GM (1,1) model. Modern Computer. 29 (4): 44-48. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C44YLTlOAiTRKibYlV5Vjs7ioT0BO4yQ4m_mOgeS2ml3UAagdcJykme-B7qa_5UmRmeoYezRlfDlSlQtgI02glnX&uniplatform=NZKPT&src=copy
[5]
Wang, C. J., Meng, Y. J. 2022. Prediction of Civil Aviation Passenger Traffic Volume Based on Seasonal ARIMA Model. Statistics and Management. 37 (05): 88-93. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C44YLTlOAiTRKibYlV5Vjs7ioT0BO4yQ4m_mOgeS2ml3UOhddwtjwT2mDxqoJR7On3W2RDwzAvxfHCgLWv42mOjz&uniplatform=NZKPT&src=copy
[6]
Li, X., Zhou, X. M., Wu, X. F. 2023. Forecast on Passenger Traffic Volume of Civil Aviation Based on HW-EEMD-SVM Model.The Journal of Quantitative Economics. 14 (02): 189-204. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C44wp2hFvIb_zkhNKwLndgnd1biDbp3Ix89Q7Vx0qi0-jBiWUBQcpcet7EHIlF6E5gXcGrG8-kH4jknYQDkI37wM&uniplatform=NZKPT&src=copy
[7]
Cui, J., Dang, Y. G., Liu, S. F. 2009. Novel grey forecasting model and its modeling mechanism. Control and Decision, 24(11):1702-1706. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C44YLTlOAiTRKgchrJ08w1e75TZJapvoLK0_Y4adPyNTbtz6mfyRmnQY_yOgsy3_If9LDeqwk8v-5eL4bXiu5yBP&uniplatform=NZKPT&src=copy
[8]
Qian, W. Y., Dang, Y. G., Liu, S. F. 2012. Grey GM (1,1,) model with time power and its application. Systems Engineering-Theory & Practice, 32(10):2247-2252. https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C44YLTlOAiTRKgchrJ08w1e7fm4X_1ttJAlHuDoz186n_xb5iUKygUdz6W83Efe9w7CnfexCvIDI-Wnb2FZNVl0U&uniplatform=NZKPT&src=copy
[9]
Luo, D., Wei, B. L. 2017. Grey forecasting model with polynomial term and its optimization. Journal of Grey System, 29(3):58-69.
[10]
Wei, B. L., Xie, N. M., Hu, A. Q. 2018. Optimal solution for novel grey polynomial prediction model. Applied Mathematical Modeling, 62:717-727.
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Information
Published In
November 2023
902 pages
ISBN:9798400716485
DOI:10.1145/3653081
Copyright © 2023 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 03 May 2024
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IoTAAI 2023
IoTAAI 2023: 2023 5th International Conference on Internet of Things, Automation and Artificial Intelligence
November 24 - 26, 2023
Nanchang, China
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