Port Throughput Prediction based on ARIMA Model and Holt-Winters Exponential Smoothing Method
DOI:
https://doi.org/10.62051/ajmse.v1n3.04Keywords:
Port Throughput Forecasting, Shanghai Port, ARIMA Model, Holt-Winters Exponential SmoothingAbstract
Port throughput is a key indicator of port operation efficiency and economic contribution. Accurate forecasting helps improve port management and risk control. This paper uses monthly container throughput data of Shanghai Port from 2013 to 2023 to compare the ARIMA model and Holt-Winters exponential smoothing method. After trend and stationarity tests, ARIMA (1,1,2), Holt-Winters additive, and multiplicative models are constructed. Model performance is evaluated using MAE, RMSE, and MAPE. The results show that the Holt-Winters multiplicative model performs best and is used to forecast throughput from January to June 2025.
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[1] Liu, M. M., & Jiang, Y. (2021). Research on port throughput forecasting based on an improved multilayer perceptron model. Software Engineering, (3), 39-42+35.
[2] Liu, Y. Q., & Zeng, M. (2018). Research on forecasting methods for port container throughput. Logistics Engineering and Management, (8), 85-87.
[3] Wang, F. W., Zhang, X. B., Yan, J. C., & Ji, Z. (2022). Forecasting container throughput of Shanghai Port based on LSTM. Navigation of China, 45(2), 109-114.
[4] Gao, Y., Zhou, J. H., Wang, H. T., & Zhang, H. H. (2020). Forecasting Chinese port container throughput based on the Jackknife model averaging method. Journal of Systems Science and Mathematical Sciences, (4), 729-737. [in Chinese]
[5] Tang, T. C., & Li, L. (2020). Forecasting Shanghai Port container throughput based on a grey Markov model. Logistics Sci-Tech, (3), 105-108+114.
[6] Xiao, J., Wen, Z., Liu, B., Li, C. Y., Wang, Y. D., & Huang, J. (2022). Research on a hybrid forecasting model for container throughput based on selective deep ensemble learning. Systems Engineering—Theory and Practice, (4), 1107-1128.
[7] Ayesha, U., Farookh, H., & Muhammad, S. (2021). Container shipment demand forecasting in the Australian shipping industry: A case study of the Asia-Oceania trade lane. Journal of Marine Science and Engineering, 9(9), 968. https://doi.org/10.3390/jmse9090968.
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