基于机器学习的船舶能耗智能预测方法验证分析

船舶能耗智能预测是实现船舶能效智能评估与优化决策的基础和前提。大数据、人工智能、机器学习等新兴技术促进了船舶能耗预测方法的不断发展，为分析不同基于机器学习的船舶能耗预测算法的预测精度与效果，进行了不同预测算法的实例验证分析。结合船舶油耗及其影响因素实船采集数据，通过采用不同机器学习算法对船舶能耗进行预测分析，验证了各算法的特点和优势，从而为选择合适的船舶能耗预测算法提供参考。

Verification and analysis of intelligent prediction method of ship energy consumption based on machine learning

The intelligent prediction of ship energy consumption is the basis and premise of intelligent assessment and optimization of ship energy efficiency. Emerging technologies such as big data, artificial intelligence and machine learning have continuously promoted the development of forecasting methods for the ship energy consumption. The validation analysis of different machine learning based prediction algorithms of ship energy consumption was carried out with actual examples, in order to analyze the Prediction accuracy and effect of these algorithms. The ship energy consumption was predicted by adopting different machine learning algorithms based on the energy consumption and its influencing factor data collected from the actual ship. The characteristics and advantages of these algorithms are verified and analyzed through a case study, thus providing a reference for choosing the most suitable algorithm for the ship energy consumption prediction.