Prediction of ship fuel consumption based on broad learning system

doi:10.1109/SPAC49953.2019.237871

Status	已發表Published
	Prediction of ship fuel consumption based on broad learning system
	Li，Xinyu 1; Zhu，Yongjie 1; Zuo，Yi 1; Li，Tieshan 1; Chen，C. L.P.2
	2019-12-01
Source Publication	2019 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2019
Pages	54-58
Abstract	With the increasing attention of IMO to green shipping, and the increasingly strict restrictions on fuel regulatory and operating costs of shipping enterprises, no matter from the perspective of energy conservation and environmental protection or operating economy, ships should be put into actual operations in the future with lower fuel consumption and less emissions. At present, the researches and applications of maritime big data are mostly concentrated in the field of shipping schedules and cargoes. However, there are few studies focusing on the ship energy management. This paper proposes a fuel consumption prediction model based on the Broad Learning System (BLS) and the Danish RO-RO ship Ms Smyril is taken as the case ship. With the measured operation data, the fuel consumption prediction model of the ship is constructed by using data analysis and machine learning. Finally, compared with the existing fuel consumption prediction methods, it is proved that the prediction effects of this method are better. The rapidity of BLS can be used for real-time prediction of fuel consumption. When there are some mechanical failures of the ship which may cause the abnormal fuel consumption of the ship, it can help the engineers and the deck officers response quickly and address problems in time. It can also provide decision-making basis for navigation optimization.
Keyword	Broad Learning System Data analysis Prediction offuel consumption Shipping
DOI	10.1109/SPAC49953.2019.237871
URL	View the original
Language	英語English
Scopus ID	2-s2.0-85086236089
Fulltext Access	View Full-Text via DOI View Full-Text via Scopus
Citation statistics
Document Type	Conference paper
Collection	University of Macau
Corresponding Author	Chen，C. L.P.
Affiliation	1.Dalian Maritime University,Navigation College,Dalian,China 2.1 University of MacauSouth China,University of Technology,Faculty of Science and Technology,Macao
Corresponding Author Affilication	Faculty of Science and Technology
Recommended Citation GB/T 7714	Li，Xinyu,Zhu，Yongjie,Zuo，Yi,et al. Prediction of ship fuel consumption based on broad learning system[C], 2019, 54-58.
APA	Li，Xinyu., Zhu，Yongjie., Zuo，Yi., Li，Tieshan., & Chen，C. L.P. (2019). Prediction of ship fuel consumption based on broad learning system. 2019 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2019, 54-58.

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