Research on Time Series Forecasting Method Based on Autoregressive Integrated Moving Average Model with Zonotopic Kalman Filter

Xiaopu Zhang and Wenbin Cao ()
Additional contact information
Xiaopu Zhang: School of Business, Jiangnan University, Wuxi 214122, China
Wenbin Cao: School of Business, Jiangnan University, Wuxi 214122, China

Sustainability, 2025, vol. 17, issue 7, 1-19

Abstract: Ningbo Zhoushan Port and Shanghai Port, as the top two ports in China in terms of port cargo throughput, play a crucial role in facilitating international trade and shipping. The accurate forecasting of the cargo throughput at these ports is essential for the government planning of port infrastructure and for the efficient allocation of resources by shipping enterprises. This study proposes a novel combined forecasting method for port cargo throughput, integrating the Autoregressive Integrated Moving Average (ARIMA) model with the zonotopic Kalman filter (ZKF) to address the limitations of traditional forecasting models in terms of accuracy and timeliness. First, an ARIMA model is established to perform the preliminary forecasting of the cargo throughput time series, generating a state–space representation that captures the underlying patterns in the data. Subsequently, the ZKF is applied to filter the ARIMA predictions, dynamically adjusting the forecast intervals based on the hypercube feasible set to optimize the estimation of port throughput. The results indicate that the ARIMA–ZKF combined model significantly mitigates the effects of asynchrony and lag, achieving a high prediction accuracy and robustness. This innovative approach offers an effective new method for forecasting port throughput, providing valuable practical guidance for port development and resource management.

Keywords: port throughput; time series analysis; ARIMA; ZKF; combined model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/7/2993/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/7/2993/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:7:p:2993-:d:1622178

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().