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作 者:杨科 唐朝国 袁焦[1] 伏坤 邹文露 YANG Ke;TANG Chaoguo;YUAN Jiao;FU Kun;ZOU Wenlu(China Railway Eryuan Engineering Group Co.,Ltd.,Chengdu 610031,China)
机构地区:[1]中铁二院工程集团有限责任公司,成都610031
出 处:《高速铁路技术》2020年第6期45-48,57,共5页High Speed Railway Technology
摘 要:在利用计算机处理铁路工程施工日志庞大数据集合的过程中,计算时间长、内存消耗大、最终导致整个计算系统崩溃的现象时有发生,因此,亟需寻求一种可靠、高效的数据处理方式。本文利用分布式架构,采用成熟的数据分析R语言,通过对铁路工程现场施工数据进行抽取、存储和分析,以分布式计算方法实现了Apriori关联分析算法,完成了对海量现场数据的高效分析,提升了分析速度,降低了计算资源的占用。经实际工程应用验证,分析结果真实清晰地反映了现场实际,能够为施工活动提供有力的数据支撑,有效规避和降低过程风险,对铁路工程建设活动的管理具有重要参考意义。In the process of using computer to process the huge data set of railway engineering construction log,phenomena such as long calculation time,large memory consumption and collapse of the whole computing system finally caused often occur.Therefore,it is urgent to find a reliable and efficient data processing method.In this paper,the Apriori association analysis algorithm is realized with distributed computing method by using distributed architecture and mature data analysis R language through extraction,storage and analysis of railway engineering site construction data,which has been used to complete the analysis of large amounts of site data efficiently,improve the analysis speed and reduce the occupation of computing resources.It has been verified by practical engineering application that the analysis results truly and clearly reflect the actual site condition,which can provide powerful data support for construction activities,effectively avoid and reduce process risks,and have important reference significance for the management of railway engineering construction activities.
关 键 词:分布式 施工工序 关联分析 R语言 APRIORI EBS
分 类 号:TP311.1[自动化与计算机技术—计算机软件与理论]
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