A Ship Energy Consumption Prediction Method Based on TGMA Model and Feature Selection
Yuhang Liu,
Kai Wang,
Yong Lu
et al.
Abstract:Optimizing ship energy efficiency is a crucial measure for reducing fuel use and emissions in the shipping industry. Accurate prediction models of ship energy consumption are essential for achieving this optimization. However, external factors affecting ship fuel consumption have not been comprehensively investigated, and many existing studies still face efficiency and accuracy challenges. In this study, we propose a neural network model called TCN-GRU-MHSA (TGMA), which incorporates the temporal convolutional… Show more
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