Random Forest Algorithm-Based Lightweight Comprehensive Evaluation for Wireless User Perception

被引:2
|
作者
Zhang, Kaixuan [1 ]
Wang, Juan [1 ]
Zhang, Wei [2 ]
Wang, Ke [3 ]
Zeng, Jun [1 ]
Fan, Guanghui [1 ]
Gui, Guan [1 ,3 ]
机构
[1] Nanjing Univ Posts & Telecommun, Coll Telecommun & Informat Engn, Nanjing 210003, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Sch Comp Sci, Nanjing 210023, Peoples R China
[3] Yangtze Univ, Sch Elect & Informat, Jingzhou 434023, Peoples R China
基金
中国国家自然科学基金;
关键词
Comprehensive evaluation methods; wireless user perception; indicator selection; random forest (RF); COMMUNICATION; ALLOCATION; NETWORKING;
D O I
10.1109/ACCESS.2019.2956285
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The quality of wireless user perception for cells in a particular scenario is reflected on a set of indicators. Comprehensive evaluation of those cells is the base of network optimization for operators. Traditional methods use weighted sum of all indicators as the evaluation result. However, these indicators include some ineffective ones, which leads to an unconvincing evaluation result. To achieve a convincing and accurate result, we propose a lightweight comprehensive evaluation method. Firstly, indicator selection is implemented via random forest algorithm. Secondly, those selected indicators are weighted via entropy method. Finally, we compute the score of all cells with the weights. Experiment results are given to show that the cells with higher score perform better on all indicators, which is coincide with the actual situation. Hence, our proposed method is not only lightweight but also obtain more accurate result.
引用
收藏
页码:173477 / 173484
页数:8
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