基于深度学习算法的计算机网络控制系统优化设计

Optimization Design of Computer Network Control System Based on Deep Learning Algorithm

在当今的信息时代计算机网络的稳定性和效率对于个人和企业都至关重要。网络控制系统负责监控和管理网络流量、确保数据传输的安全和高效。然而,随着网络规模的扩大和应用需求的多样化,传统的网络控制技术面临诸多挑战,包括数据处理能力不足、反应速度慢、无法有效应对复杂和动态的网络环境。深度学习,作为一种能够从大量数据中自动学习和提取高层特征的算法,已经在图像识别、自然语言处理等领域展现出了强大的性能。其在网络控制系统中的应用,尤其是在流量预测、异常检测和网络安全等方面,提供了新的解决方案。

In today's information age,the stability and efficiency of computer networks are cru-cial for both individuals and businesses.The network control system is responsible for monito-ring and managing network traffic,ensuring the security and efficiency of data transmission.However,with the expansion of nctwork scale and the diversification of application require-ments,traditional network control technologies face many challenges,including insufficient data processing capabilities,slow response speed,and inability to effectively cope with complex and dynamic network cnvironments.Deep learning,as an algorithm that can automatically learn and extract high-level features from large amounts of data,has shown strong performance in fields such as image rccognition and natural language processing.Its application in network control systems,especially in traffic prediction,anomaly detcction,and network sccurity,provides new solutions.