Energy Efficiency Evaluation and Forecasting of the Sussex Ports to Address Climate Change Concerns: A Data-Driven Decision Model

Murat Aymelek, Ismail Kurt

Research output: Contribution to conferencePaperpeer-review


The economic output and societal influence of ports are vital for the economy of the Sussex region in the United Kingdom. The Sussex ports facilitate not only the movement of freight but also fishing, passenger transport, leisure, and offshore supply operations. However, the port industry cluster in Sussex is facing a number of upcoming challenges as a result of climate change and the growing demand for sustainable port operations. In this study, a data-driven mathematical model combining a multi-criteria decision-making (MCDM) framework with machine learning techniques (MLT) is proposed to compare forecasts of short and medium-term sustainability performances of ports in the Sussex cluster. The methodology of the study particularly applies the Multi-Attribute Value Analysis (MAVA) model to evaluate the performance of the Sussex ports based on the main criteria and related sub-criteria. The Autoregressive Integrated Moving Average (ARIMA) model is also used to forecast changes in the data used for the criteria for the short term (by 2025) and medium term (by 2030). The data are obtained and elaborated from an AIS data platform and other available secondary sources. The energy efficiency performance of the ports in the Sussex cluster will be revealed in terms of port operations. The early findings of this study will suggest the port with the highest MAVA score in 2023, 2025, and 2030. This information can inform the decisions of policymakers in determining which ports are best equipped to handle increases in shipping traffic and demand in the most energy-efficient way.
Original languageEnglish
Number of pages5
Publication statusPublished - 16 Jun 2023
Event11th Global Conference on Global Warming - Halic University- Sponsored by Turkish Airlines, Istanbul, Turkey
Duration: 14 Jun 202316 Jun 2023
Conference number: 11


Conference11th Global Conference on Global Warming
Abbreviated titleGCGW-2023
Internet address


Dive into the research topics of 'Energy Efficiency Evaluation and Forecasting of the Sussex Ports to Address Climate Change Concerns: A Data-Driven Decision Model'. Together they form a unique fingerprint.

Cite this