Browse by author
Lookup NU author(s): Dr Yi Zhou, Dr Kayvan PazoukiORCiD, Professor Alan Murphy
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Fuel Oil Consumption (FOC) represents a significant portion of a fishing vessel’s operating costs, often exceeding 50%. Accurately forecasting FOC during the voyage planning stage is crucial but challenging for optimizing routes and supporting decision-making systems aimed at fuel-saving. Data-driven models have shown excellent performance in FOC prediction. However, gathering the necessary data for these models is expensive and time-consuming. Even though, the applicability of FOC model derived from one vessel to predict FOC for another vessel has received limited research attention. This paper investigates the performance in predicting FOC for an unseen tuna purse seiner, using a two-stage model trained on metocean and operational data, from Copernicus and sensors installed on her similar vessel, respectively. By considering the engine performance modifications, the two-stage model trained on the similar vessel achieves high mean accuracies (over 94%) in predicting FOC for the unseen vessel.
Author(s): Zhou Y, Pazouki K, Murphy AJ
Publication type: Article
Publication status: Published
Journal: International Journal of Maritime Engineering
Year: 2025
Volume: 167
Issue: A1
Pages: 41-50
Online publication date: 27/02/2026
Acceptance date: 30/10/2025
Date deposited: 02/03/2026
ISSN (print): 1479-8751
Publisher: Royal Institution of Naval Architects
URL: https://doi.org/10.5750/ijme.v167iA1.1404
DOI: 10.5750/ijme.v167iA1.1404
ePrints DOI: 10.57711/b0xx-mz63
Altmetrics provided by Altmetric
