铁道货运2024，Vol.42Issue(6)：33-44,12.DOI:10.16669/j.cnki.issn.1004-2024.2024.06.06
基于集装箱运用数据的铁路集装箱装卸站聚类融合算法研究
Clustering Algorithm for Railway Container Handling Stations Based on Container Operation Data
摘要
Abstract
To eliminate the impact of different container applications on the quality evaluation of container manufacturing,this paper analyzed the container operation and maintenance data from the past 10 years that covered multiple factors such as transportation categories,station characteristics,and handling frequency.Based on the differences in the operation of railway container stations,a container cluster index system was constructed using container operation data.A dataset available for cluster analysis was formed through data preprocessing technology.Various clustering algorithms,such as K-means,EM,and Canopy,were utilized to comprehensively analyze the processed dataset to identify station groups with similar container operation characteristics.To overcome the potential bias of different algorithms,an algorithm fusion strategy based on the voting principle was introduced to reduce the dependence among algorithms.The results show that the fused cluster effect is superior to the effect of any single algorithm,which can provide basic data for the comprehensive analysis of railway container maintenance.关键词
铁路/综合运输/集装箱维修/数据挖掘/装卸站分析/聚类算法/融合算法Key words
Railway/Integrated Transportation/Container Maintenance/Data Mining/Analysis of Loading and Unloading Station/Cluster Algorithm/Fusion Algorithm分类
交通工程引用本文复制引用
王旭,祝凌曦,李诗林..基于集装箱运用数据的铁路集装箱装卸站聚类融合算法研究[J].铁道货运,2024,42(6):33-44,12.基金项目
中国国家铁路集团有限公司科技研究开发计划课题(K2019S010) （K2019S010）
