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Study on route division for ship energy efficiency optimization based on big environment data

Authors: Wang, K. (author); Yan, Xinping (author); Yuan, Yupeng (author); Jiang, X. (author); Lodewijks, G. (author); Negenborn, R.R. (author);

Study on route division for ship energy efficiency optimization based on big environment data

Abstract

In the case of the global energy crisis and the higher sound of energy saving and emission reduction, how to take effective management measures of ship energy efficiency to achieve the goal of energy saving and emission reduction, put forward a new challenge for the development of shipping technology. The application of big data technology provides a new idea for the research of ship energy efficiency optimization management. The energy efficiency management level of the operating ship can be improved by the analysis and mining of the big data. In this paper, a big data analysis platform for ship energy efficiency management based on the widely used Hadoop platform architecture is designed. Afterward, due to the huge amount of involved data on the energy efficiency management which has exceeded the processing ability of traditional solutions, the big data analysis method is used to achieve the route division according to environmental factors, thus to lay the foundation for speed optimization in different segments of a route. Finally, a simple decision-making method of optimal engine speed based on the result of route division is proposed, which could improve ship energy efficiency and hence reduce CO2 emission.

Country
Netherlands
Related Organizations
Keywords

Big Data, Optimization, Navigation, Energy efficiency, Marine vehicles, Environmental factors, Algorithm design and analysis

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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12
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47