has been cited by the following article(s):
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[1]
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Estimation and optimization of ship fuel consumption in maritime: review, challenges, and future directions
Journal of Marine Science and Technology,
2026
DOI:10.1007/s00773-025-01104-9
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[2]
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Ship fuel consumption prediction based on transfer learning: Models and applications
Engineering Applications of Artificial Intelligence,
2025
DOI:10.1016/j.engappai.2024.109769
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[3]
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Machine learning techniques in maritime environmental sustainability: A comprehensive review of the state of the art
Computers and Electrical Engineering,
2025
DOI:10.1016/j.compeleceng.2025.110395
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[4]
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Optimising bulk carriers' fuel efficiency: PCA and Shapley value analysis under varying wind conditions
Ocean Engineering,
2025
DOI:10.1016/j.oceaneng.2025.121976
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[5]
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Speed optimization for maximizing the ship’s economic benefits considering the Carbon Intensity Indicator (CII)
Ocean Engineering,
2024
DOI:10.1016/j.oceaneng.2024.116712
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[6]
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Algorithm for carbon emission peak prediction and emission reduction potential analysis based on convolutional neural network and multi-dimensional power big data
Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024),
2024
DOI:10.1117/12.3033162
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[7]
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Application of Intelligent Digital Technology in Load Forecasting of New Power Systems
2023 International Conference on Network, Multimedia and Information Technology (NMITCON),
2023
DOI:10.1109/NMITCON58196.2023.10276027
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[8]
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Comparison of Machine Learning Algorithms For Predicting CO2Emissions in the maritime domain
2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA),
2023
DOI:10.1109/IISA59645.2023.10345936
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