文章摘要
基于LSTM神经网络的船舶油耗模型研究
Research on ship fuel consumption model based on LSTM neural network
投稿时间:2024-02-02  修订日期:2024-03-05
DOI:
中文关键词: 油耗预测  黑箱模型  数据预处理  LSTM神经网络
英文关键词: fuel consumption prediction  black-box model  data preprocessing  LSTM neural network
基金项目:国家自然基金项目支持(52071059)
作者单位
李智东 大连理工大学工程装备结构分析国家重点实验室 船舶工程学院 
易文欣 大连理工大学工程装备结构分析国家重点实验室 船舶工程学院 
陆丛红* 大连理工大学工程装备结构分析国家重点实验室 船舶工程学院 
周波 大连理工大学工程装备结构分析国家重点实验室 船舶工程学院 
摘要点击次数: 58
全文下载次数: 0
中文摘要:
      针对船舶节能减排和提高经济效益的需求,建立了准确的船舶油耗模型,为船舶采取各种航行优化措施提供了决策基础。基于丹麦籍客滚轮的实测运行数据,经过数据预处理和特征选取,利用LSTM神经网络和多种机器学习算法建立了案例船的黑箱油耗模型。将各模型对测试集和额外时间序列测试集的预测值与真实值分别进行比较,结果表明LSTM模型对两种测试集的预测误差均低于1.3%,预测精度不会出现较大波动;而其它模型对时间序列数据的预测性能会下降,稳定性和预测精度均不如LSTM模型。考虑到油耗模型的预测性能和实际应用场景,基于LSTM神经网络的油耗模型具有较大的优势,对后续的船舶油耗预测及航行策略优化都具有重要意义。
英文摘要:
      In response to the demand for energy saving and emission reduction of ships and improvement of economic benefits, an accurate ship fuel consumption model is established, which provides a decision-making basis for ships to take various navigation optimization measures. Based on the measured operational data of a Danish passenger ro-ro ship, after data preprocessing and feature selection, the black box fuel consumption model of the case ship was established using LSTM neural network and various machine learning algorithms. The prediction values of each model for the test set and the additional time series test set are compared with the real values respectively, and the results show that the prediction errors of the LSTM model for both test sets are lower than 1.3%, and the prediction accuracy does not fluctuate greatly; whereas, the prediction performance of the other models for the time series data decreases, and the stability and prediction accuracy are not as good as that of the LSTM model. Considering the prediction performance of the fuel consumption model and the practical application scenarios, the fuel consumption model based on LSTM neural network has a greater advantage, which is of great significance for the subsequent prediction of fuel consumption of ships and the optimization of sailing strategies.
View Fulltext   查看/发表评论  下载PDF阅读器
关闭