摘要
传统的交换机决策算法主要基于固定的规则和策略,难以适应复杂多变的网络环境。随着人工智能技术的快速发展,机器学习和深度学习算法成为改进交换机决策的有力工具。这些算法能够通过学习和训练来自动调整交换机的决策策略,提高网络的效率和可靠性。主要介绍基于人工智能的计算机网络交换机决策算法的理论基础、应用技术和算法设计,以及几种具体的算法示例。
The traditional decision algorithm of switches is mainly based on fixed rules and strategies and is difficult to adapt to the complex and changeable network environment.With the rapid development of artificial intelligence technology,machine learning and deep learning algorithms have become powerful tools for improving the decision of switches,which can automatically adjust the decision strategy of switches through learning and training and im⁃prove the efficiency and reliability of the network.This article mainly introduces the theoretical basis,application technology and algorithm design of the decision algorithm of computer network switches based on artificial intelli⁃gence,as well as several specific algorithm examples.
作者
阎志峰
沈玥
刘佳帆
刘威
YAN Zhifeng;SHEN Yue;LIU Jiafan;LIU Wei(Taiyuan Satellite Launch Center,Taiyuan,Shanxi Province,030027 China;Beijing Institute of Tracking and Telecommunications Technology,Beijing,100094 China)
出处
《科技资讯》
2024年第11期74-76,共3页
Science & Technology Information
关键词
人工智能
计算机网络交换机
决策算法
深度学习
Artificial intelligence
Computer network switch
Decision algorithm
Deep learning
