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Study on route division for ship energy efficiency optimization based on big environment data
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.
- Wuhan University of Technology China (People's Republic of)
- Wuhan Polytechnic University China (People's Republic of)
- Delft University of Technology Netherlands
- Wuhan Polytechnic University China (People's Republic of)
Big Data, Optimization, Navigation, Energy efficiency, Marine vehicles, Environmental factors, Algorithm design and analysis
Big Data, Optimization, Navigation, Energy efficiency, Marine vehicles, Environmental factors, Algorithm design and analysis
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).12 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.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10% visibility views 14 download downloads 47 - 14views47downloads
Data source Views Downloads TU Delft Repository 14 47


