Prediction of harbour vessel fuel consumption based on machine learning approach
Fuel consumption influences both the economic and environmental perspectives of shipping. With the help of machine learning, meaningful knowledge and complex relationships can be extracted from high-dimensional historical data. In this study, machine learning models were developed to predict the fue...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/169945 |
| _version_ | 1811696259009871872 |
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| author | Chen, Zhong Shuo Lam, Jasmine Siu Lee Xiao, Zengqi |
| author2 | School of Civil and Environmental Engineering |
| author_facet | School of Civil and Environmental Engineering Chen, Zhong Shuo Lam, Jasmine Siu Lee Xiao, Zengqi |
| author_sort | Chen, Zhong Shuo |
| collection | NTU |
| description | Fuel consumption influences both the economic and environmental perspectives of shipping. With the help of machine learning, meaningful knowledge and complex relationships can be extracted from high-dimensional historical data. In this study, machine learning models were developed to predict the fuel consumption of harbour vessels with ship-related and meteorological factors. The superiority of machine learning models over statistical linear regression model (Ridge regression) has been proved. This study further investigated whether the use of meteorological factors enhances the prediction of fuel consumption. A case study on the prediction of tugboat fuel consumption was conducted. The Random Forest model outperformed the other models. Comparative experiments showed that meteorological factors collectively add value to the fuel consumption prediction, which enhances the accuracy from 0.7 to 38.9%. The potential uses of the prediction results are highlighted in terms of both operational management and environmental evaluation aspects. |
| first_indexed | 2024-10-01T07:36:31Z |
| format | Journal Article |
| id | ntu-10356/169945 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:36:31Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1699452023-08-15T08:14:06Z Prediction of harbour vessel fuel consumption based on machine learning approach Chen, Zhong Shuo Lam, Jasmine Siu Lee Xiao, Zengqi School of Civil and Environmental Engineering Maritime Energy and Sustainable Development Centre of Excellence Engineering::Environmental engineering Machine Learning Harbour Vessel Fuel consumption influences both the economic and environmental perspectives of shipping. With the help of machine learning, meaningful knowledge and complex relationships can be extracted from high-dimensional historical data. In this study, machine learning models were developed to predict the fuel consumption of harbour vessels with ship-related and meteorological factors. The superiority of machine learning models over statistical linear regression model (Ridge regression) has been proved. This study further investigated whether the use of meteorological factors enhances the prediction of fuel consumption. A case study on the prediction of tugboat fuel consumption was conducted. The Random Forest model outperformed the other models. Comparative experiments showed that meteorological factors collectively add value to the fuel consumption prediction, which enhances the accuracy from 0.7 to 38.9%. The potential uses of the prediction results are highlighted in terms of both operational management and environmental evaluation aspects. Nanyang Technological University Singapore Maritime Institute (SMI) Authors acknowledge Nanyang Technological University’s research scholarship to the first author as a PhD student. The research is also supported by Singapore Maritime Institute through Maritime Energy and Sustainable Development (MESD) Centre of Excellence. 2023-08-15T08:14:05Z 2023-08-15T08:14:05Z 2023 Journal Article Chen, Z. S., Lam, J. S. L. & Xiao, Z. (2023). Prediction of harbour vessel fuel consumption based on machine learning approach. Ocean Engineering, 278, 114483-. https://dx.doi.org/10.1016/j.oceaneng.2023.114483 0029-8018 https://hdl.handle.net/10356/169945 10.1016/j.oceaneng.2023.114483 2-s2.0-85152131459 278 114483 en Ocean Engineering © 2023 Elsevier Ltd. All rights reserved. |
| spellingShingle | Engineering::Environmental engineering Machine Learning Harbour Vessel Chen, Zhong Shuo Lam, Jasmine Siu Lee Xiao, Zengqi Prediction of harbour vessel fuel consumption based on machine learning approach |
| title | Prediction of harbour vessel fuel consumption based on machine learning approach |
| title_full | Prediction of harbour vessel fuel consumption based on machine learning approach |
| title_fullStr | Prediction of harbour vessel fuel consumption based on machine learning approach |
| title_full_unstemmed | Prediction of harbour vessel fuel consumption based on machine learning approach |
| title_short | Prediction of harbour vessel fuel consumption based on machine learning approach |
| title_sort | prediction of harbour vessel fuel consumption based on machine learning approach |
| topic | Engineering::Environmental engineering Machine Learning Harbour Vessel |
| url | https://hdl.handle.net/10356/169945 |
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