基于机器学习算法的网络质量运行预测

A. Osin, O. Sheluhin
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引用次数: 0

摘要

本文提出了一种使用流行的机器学习方法——决策树来预测计算机网络质量问题的解决方案。考虑了web服务器运行时网络质量问题的真实案例。在对网络运行过程中记录的流量进行分析的基础上,当发现网络中存在问题时,构建决策树。利用得到的模型,进行了数值实验,预测了用户打开网页出现问题的时刻。最后给出了预测模型质量的评价结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Network Quality Operation Prediction Based on Machine Learning Algorithms
The article proposes a solution to the problem of predicting the quality of a computer network using a popular machine learning method - a decision tree. Considered a real case of quality problems in the network when the web server is running. Based on the analysis of traffic recorded during the operation of the network, when problems were observed in it, a decision tree was constructed. Using the obtained model, numerical experiments were carried out to predict the moments when users have problems opening web pages. The results of assessing the quality of the prediction model obtained are given.
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