| 基于线状特性的大数据地铁用户识别与定位方法 |
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| 引用本文： | 叶婉玲.基于线状特性的大数据地铁用户识别与定位方法[J].电信工程技术与标准化,2019,32(8). |
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| 作者姓名： | 叶婉玲 |
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| 作者单位： | 中国移动通信集团广东有限公司,广州,510623 |
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| 摘 要： | 从MR原始数据特性出发研究数据结构与字段,采用基于线状特性分析MR大数据的地铁用户识别过滤方法和位置定位方法,该方法经过验证能够有效输出地铁用户数据并定位在地图上,解决人工地铁测试效率低且测试片面的问题,实现基于大数据的自动化地铁网络评估,提供海量的有效定位数据用于地铁评估与分析。
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| 关 键 词： | 线状特性 大数据 用户识别 MR数据 |
| 收稿时间： | 2019/5/18 0:00:00 |
| 修稿时间： | 2019/5/31 0:00:00 |
The method of big data subway user identification and location based on linear characteristics |
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| Ye Wan-ling.The method of big data subway user identification and location based on linear characteristics[J].Telecom Engineering Technics and Standardization,2019,32(8). |
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| Authors: | Ye Wan-ling |
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| Affiliation: | China mobile communication group guangdong Co. LTD,Guangzhou,510623 China |
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| Abstract: | Starting from the characteristics of MR raw data, the data structure and fields are studied. The Metro user identification filtering method and location positioning method based on motion analysis of MR large data are adopted. The method can effectively output Metro user data and locate them on the map. The problem of low test efficiency and one-sided test of artificial Metro is solved, and the automatic Metro Network Evaluation Based on large data is realized. To provide a large number of effective iron user data for indoor evaluation and analysis. |
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| Keywords: | Motion characteristics Big data User identification MR data |
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