摘要
目前网络优化问题仍然基本依靠手工处理,存在着效率低下、效果难以有效保证的问题.在工作量快速增长的背景下,迫切需要提高自动化和智能化水平.本文对利用机器学习提高优化工作效率和质量进行了研究,提出了机器学习在自动问题检测、自动根因分析和智能优化方案制定等方面的应用设想,给出了监督学习和非监督学习的应用方法,并提供了两个具体应用案例.
At present,mobile network optimization is still basically handled by hand,which is inefficient and difficult to guarantee the effectiveness.With the rapid growth of workload,there is an urgent need to increase the degree of automation and intelligence in optimization work.How to use machine learning in network optimization was studied,3 machine learning applications including automatic problem detection,automatic root cause analysis and intelligent solution planning were proposed,the supervised learning and unsupervised learning method with 2 cases were given.
作者
吴宝栋
费明
饶文涛
陈爽
刘大洋
方琳
WU Bao-dong;FEI Ming;RAO Wen-tao;CHEN Shuang;LIU Da-yang;FANG Lin(China Mobile Group Guangdong Co.,Ltd.,Guangzhou 510000,China)
出处
《电信工程技术与标准化》
2018年第A01期53-57,共5页
Telecom Engineering Technics and Standardization
关键词
无线网络优化
机器学习
聚类
标签
CNN
mobile network optimization
machine learning
clustering
label
CNN
