摘要
由机器人与机器学习每日新闻的新闻记者兼工作人员新闻编辑-调查人员讨论人工智能的新发现。根据NewsRx编辑对南洋理工大学的新闻报道，研究表明：“本文首先利用机器学习算法S提取校园网络流量的特征，然后引入多注意机制来融合不同尺度的海量特征。”我们的新闻记者引用了南洋理工大学的一篇研究：“利用无监督学习提出了一种网络流量异常检测方法，并进行了仿真实验，结果表明机器学习算法的检测率均在80%以上，虚警率基本在10%以下。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators discuss new findings in artificial intelligence. According to news reporting out of Nanyang Technological Universit y by NewsRx editors, research stated, “In this paper, machine learning algorithm s are first utilized to extract features of campus network traffic, and then the multi-attention mechanism is introduced to fuse the massive features extracted at different scales.” Our news reporters obtained a quote from the research from Nanyang Technological University: “Unsupervised learning is used to propose a method for detecting ne twork traffic anomalies, and simulation experiments are conducted to verify the model’s performance. The results show that the detection rates of machine learni ng algorithms are all above 80%, the false alarm rate basically sta ys below 10%.”
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