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data-driven-ship-fuel-efficiency-modeling

This projects adopts machine learning models to quantify the daily/hourly bunker fuel consumption of a ship in different sailing speed, displacement/draft, trim, weather, and sea conditions. The industry data utilized include voyage report data, sensor data, AIS data, and meteorological data. Apart from Python code, here, we also share 130 trained machine learning models that enable you to estimate the daily/hourly fuel consumption of eight 8100-TEU to 14,000-TEU containerships. To download our trained machine learning mdoels and use them for estimate/forecost ship fuel consumption rate (ton/day, ton/hour), read "Instructions on How to Use Trained Machine Learning Models". For our Python code, read "Readme - Organization of Python Code Files in This Project".

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paper

Code and data instances in my papers

tutorials

Tutorials for educational purposes