基于机器学习的4G网络工程质量评估

Quality Evaluation of 4G Network Project Based on Machine Learning

针对4G网络工程质量评估存在不全面、主观性过强等问题,提出了基于Adaboost机器学习的4G网络工程质量评估方法。首先根据4G网络工程质量评价体系确定评估指标,然后采用主成分分析从原始质量评估指标特征中提取有效指标特征,减少指标之间的相关性,最后通过建立基于Adaboost机器学习的4G网络工程质量评估模型,实现对4G网络工程质量的自动评估。实验结果表明,该方法具有更好的泛化性能,能够明显提高4G网络工程质量的评估准确率,对解决工程质量问题具有重要的理论价值和现实意义。

Considering that quality evaluation of 4G network project exists incomplete and subjective, a method based on Adaboost machine learning is proposed. Firstly, the evaluation indicators are determined according to the 4G network project quality evaluation system, then the principal component analysis is used to extract the effective from the original quality evaluation indicators characteristics, and reduce the correlation between the indicators. Finally, the model based on Adaboost machine learning is established to achieve automatic evaluation of 4G network project quality. The experimental results show that this method has better generalization performance, can significantly improve the accuracy of 4G network project quality evaluation, and has important theoretical and practical significance for solving project quality problems.