6G网络设计中基于信号强度的降雨分类机器智能方法

Vivek Kumar, Hitesh Singh, Kumud Saxena, B. Bonev, R. Prasad, V. Kapse
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引用次数: 0

摘要

由于一些基本需求,包括更高的数据速率、更大的容量、更低的延迟和更好的QoS,科学家、移动提供商行业代表和学术界已经开始研究6G通信网络(服务质量)的进步(技术)。为了创建6G移动通信的技术基础,最近开发了许多涉及重要移动基础设施供应商、学术界和全球网络运营商的研究计划或项目。本文提出了一种基于人工神经网络的智能模型。该模型的测量精度为97.6%,高于其他模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Intelligence Method for Rain Classification by Using Signal Strength for Designing of 6G Networks
As a result of some fundamental needs, including greater data rates, expanded capacity, decreased latency, and improved QoS, scientists, mobile provider industry representatives, and academia have started to look into the advancement (technical) toward 6G communication networks (Quality of Service). In an effort to create the technological foundation for 6G mobile communication, numerous research initiatives or projects involving significant mobile infrastructure suppliers, academia, and global network operators has recently been developed. In this paper, an intelligent model based on ANN is proposed. The model's measured accuracy was 97.6%, which was higher than others models.
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