摘要
探讨人工智能技术在移动通信网络中的能耗优化实现路径。通过分析深度学习、大数据分析、智能化能耗管理系统及边缘计算与云计算技术的协同优化,揭示如何利用技术手段显著降低移动通信网络能耗,提高网络效率和稳定性。最后,提出基于深度学习的流量预测和能耗优化、融合大数据分析与人工智能技术的综合优化、构建智能化能耗管理系统以及利用边缘计算与云计算技术的协同优化4个方面的具体实现路径,并深入分析每种方法的实现过程和技术优势。
This paper discusses the realization path of energy consumption optimization of artificial intelligence technology in mobile communication network.By analyzing the collaborative optimization of deep learning,big data analysis,intelligent energy management system,edge computing and cloud computing technology,this paper reveals how to significantly reduce the energy consumption of mobile communication networks and improve network efficiency and stability by using technical means.Finally,it puts forward four specific implementation paths,namely,traffic forecasting and energy consumption optimization based on deep learning,comprehensive optimization integrating big data analysis and artificial intelligence technology,building an intelligent energy consumption management system and collaborative optimization using edge computing and cloud computing technology,and deeply analyzes the implementation process and technical advantages of each method.
作者
欧阳剑
贺琦雯
OUYANG Jian;HE Qiwen(Zhengzhou Information Engineering Vocational College,Zhengzhou 450000,China)
出处
《通信电源技术》
2024年第21期132-134,共3页
Telecom Power Technology
基金
郑州信息工程职业学院科学研究项目(科技攻关类)“人工智能赋能教育研究”(KJZZ2024-0602)。
关键词
人工智能
移动通信网络
能耗优化
机器学习
网络效率
artificial intelligence
mobile communication network
energy consumption optimization
machine learning
network efficiency
