交通信息与安全2025，Vol.43Issue(1)：97-106,10.DOI:10.3963/j.jssn.1674-4861.2025.01.009
面向能效优化的内河航道智能划分方法
Intelligent Segmentation Method of Inland Waterway for Energy Efficiency Optimization
摘要
Abstract
The automatic scientific segmentation of inland waterways is significant to enhancing the accuracy of ship energy efficiency models.To address the problem of low accuracy in fuel consumption and speed prediction models built based on conventional waterway segmentation for energy efficiency optimization,an intelligent seg-mentation method of inland waterways aimed at optimizing energy efficiency is studied.The method incorporates the influence of navigational environmental parameters on ship energy performance into the clustering process by normalizing the data and calculating correlation coefficients between environmental parameters and energy efficien-cy indicators.The K-means clustering algorithm is employed to segment the entire route into multiple sections.For each segment,Random Forest algorithm is used to establish models for fuel consumption and ship speed prediction.The optimal number of clusters is determined by minimizing the overall mean absolute percentage error(MAPE)of the energy efficiency models.A case study involving an inland bulk carrier is conducted to demonstrate the applica-tion and validate the effectiveness of the proposed method,along with an analysis of the influence of data volume on the model accuracy.The results show that optimizing the number of clusters significantly improves model accura-cy:in the firstly voyage,the comprehensive MAPE of the energy efficiency model is reduced from 3.53%to 3.32%.Increasing the volume of energy-related data used in model construction further enhances the performance:when the dataset expanded from one voyage to five,the comprehensive MAPE decreased from 3.32%to 1.65%.The opti-mal number of clusters varies with different datasets,and selecting an optimal number of clusters based on multi-voyage data leads to the optimal waterway segmentation.Compared to the conventional segmentation meth-od,the proposed approach reduced the comprehensive MAPE of energy efficiency model by 0.54%,validating the effectiveness of the method in improving the prediction accuracy of ship energy efficiency model.关键词
能效优化/内河船舶/航段划分/K-means聚类算法Key words
energy efficiency optimization/inland ships/waterway segmentation/K-means clustering algorithm分类
交通工程引用本文复制引用
张瀚宇,尹奇志,王春英,钱巍文,张露,秦乐天..面向能效优化的内河航道智能划分方法[J].交通信息与安全,2025,43(1):97-106,10.基金项目
国家重点研发计划项目(2022YFB4300803)、工信部高技术船舶科研项目(MC-202002-C03)、潍柴动力股份有限公司技术项目(WCDL-GH-2021-0050)资助 （2022YFB4300803）
