公交GPS历史轨迹数据挖掘方法研究与应用  

Research and Application of Public Transit GPS Historical Trajectory Data Mining Method

作　　者：程婷婷 CHENG Tingting(Beijing CHJ Information Technology Co.,Ltd.,Beijing,101319 China)

机构地区：[1]北京车和家信息技术有限公司,北京101319

出　　处：《科技资讯》2024年第13期33-35,共3页Science & Technology Information

摘　　要：通过分析公交数据更新的基本要素和挖掘类型,利用大数据挖掘原理,结合公交GPS历史数据的特点,提出了适用于公交GPS历史数据挖掘和更新的专用方法和算法,并引入机器学习模型提升挖掘算法能力,在此基础上设计了挖掘作业流程,通过结果对比,可得出在数据优化周期内,可作业率由15%提升至50%,线上数据更新频率由周级更新变为天级更新。以上数据挖掘方法和算法有效提高了更新效率,改进了更新准确率,在公交数据更新作业中发挥了重要作用,方便了公交用户出行,并助力绿色出行。By analyzing the basic elements and mining types of bus data updating,by using the principle of big data mining and combining the characteristics of bus GPS historical data,in this paper,a special method and algorithm for historical data mining and updating of public transit GPS is proposed,and a machine learning model is introduced to improve the mining algorithm ability.On this basis,a mining workflow was designed,and through the comparison of results,it can be concluded that in the data optimization cycle,the work rate can be increased from 15% to 50%,online data update frequency from weekly update to day update.The above data mining methods and algorithms effectively improve the update efficiency,improve the update accuracy,play an important role in bus data update operations,convenient for bus users to travel,promoting green travel.

关 键 词：公交GPS历史数据 大数据挖掘 挖掘算法 模型评价 数据更新 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]