深度学习在网络流量分析与优化中的应用研究  

Research on the Application of Deep Learning in Network Traffic Analysis and Optimization

作　　者：王涛 WANG Tao(State Grid Shanxi Electric Power Company Jinzhong Power Supply Company,Jinzhong 030600,China)

机构地区：[1]国网山西省电力公司晋中供电公司,山西晋中030600

出　　处：《通信电源技术》2024年第10期220-222,共3页Telecom Power Technology

摘　　要：随着互联网技术的迅猛发展,传统网络流量分析方法受限于人工规则设定和处理复杂模式的能力,难以适应现代网络环境的动态性和复杂性。深度学习作为人工智能领域的前沿技术,因其出色的特征学习和模式识别能力,在网络流量分析与优化领域展现出巨大的应用潜力。文章围绕深度学习技术在网络流量分析与优化中的应用进行深入研究,旨在探讨其提升网络性能、保障网络安全以及提高资源利用率的可能性和有效性。With the rapid development of internet technology,traditional network traffic analysis methods are limited by the ability of manual rule setting and complex mode processing,which is difficult to adapt to the dynamic and complex nature of modern network environment.Deep learning,as a cutting-edge technology in the field of artificial intelligence,has shown enormous potential for application in network traffic analysis and optimization due to its excellent feature learning and pattern recognition capabilities.This article conducts in-depth research on the application of deep learning technology in network traffic analysis and optimization,aiming to explore its possibilities and effectiveness in improving network performance,ensuring network security,and improving resource utilization.

关 键 词：深度学习 网络流量分析 网络优化 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]