| 基于机器学习的无线网络用户感知速率智能预测研究 |
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| 引用本文： | 王科,袁满,杨宗林. 基于机器学习的无线网络用户感知速率智能预测研究[J]. 电信工程技术与标准化, 2020, 0(2): 25-30 |
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| 作者姓名： | 王科 袁满 杨宗林 |
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| 作者单位： | 中国联合网络通信有限公司山东省分公司,中国联合网络通信有限公司山东省分公司,中国联合网络通信有限公司山东省分公司 |
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| 摘 要： | 本文利用人工智能算法,结合DT/CQT、SpeedVideo、某厂家专有平台用户感知栅格速率数据,并关联栅格内覆盖、质量、负荷、性能等指标作为训练样本,分析影响用户感知速率的关键因素。通过建立预测用户感知速率的算法模型,实现栅格粒度用户感知速率预测,快速精准定位用户体验短板,有的放矢的解决用户体验问题,实现网络竞争力持续提升。
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| 关 键 词： | 人工智能 机器学习 用户感知速率 栅格评估 |
| 收稿时间： | 2019-12-11 |
| 修稿时间： | 2020-01-19 |
Research on Intelligent Prediction of User Perception Rate in Wireless Network Based on Machine Learning |
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| Wang Ke,Yuan Man and Yang Zonglin. Research on Intelligent Prediction of User Perception Rate in Wireless Network Based on Machine Learning[J]. Telecom Engineering Technics and Standardization, 2020, 0(2): 25-30 |
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| Authors: | Wang Ke Yuan Man Yang Zonglin |
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| Affiliation: | China Unicom Network#$NBSCommunications Co.,Ltd,Shandong Branch,China Unicom Network#$NBSCommunications Co.,Ltd,Shandong Branch,China Unicom Network#$NBSCommunications Co.,Ltd,Shandong Branch |
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| Abstract: | Using artificial intelligence algorithm, based on DT/CQT, SpeedVideo and Huawei discovery platform data which support grid granularity, and parameters of grid granularity coverage, quality, load and performance as training data. That can analysis key factors affecting user perception rate. Algorithm model of predicting user perception was established to achieve grid granularity user perception rate prediction, rapid and accurate positioning of user experience short board, targeted solution to user experience problems, and continuous improvement of network competitiveness. |
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| Keywords: | Artificial Intelligence Machine LearningS SUser Perception Rate Grid Assessment |
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