Artificial intelligence for reducing the carbon emissions of 5G networks in China

IF 25.7 1区环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Nature Sustainability Pub Date : 2023-08-17 DOI:10.1038/s41893-023-01208-3

引用次数: 0

Abstract

A data-driven framework has been developed to assess the carbon emissions of mobile networks in China, revealing that the launch of 5G networks leads to a decline in carbon efficiency. A deep reinforcement learning algorithm, DeepEnergy, is proposed to increase the carbon efficiency of mobile networks and reduce carbon emissions.

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

人工智能减少中国 5G 网络的碳排放

我们开发了一个数据驱动的框架来评估中国移动网络的碳排放，发现 5G 网络的推出导致了碳效率的下降。研究提出了一种深度强化学习算法--DeepEnergy，以提高移动网络的碳效率并减少碳排放。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Nature Sustainability Energy-Renewable Energy, Sustainability and the Environment

CiteScore

41.90

自引率

1.10%

发文量

159

期刊介绍： Nature Sustainability aims to facilitate cross-disciplinary dialogues and bring together research fields that contribute to understanding how we organize our lives in a finite world and the impacts of our actions. Nature Sustainability will not only publish fundamental research but also significant investigations into policies and solutions for ensuring human well-being now and in the future.Its ultimate goal is to address the greatest challenges of our time.

期刊最新文献

Pick the low-hanging fruit first Landscape of litigation in the United States Outcomes and policy focus of environmental litigation in the United States Balancing rights Impacts of climate litigation on firm value