移动通信核心网中基于机器学习的用户行为分析与优化
User Behavior Analysis and Optimization Based on Machine Learning in Mobile Communication Core Network
朱若冲1
作者信息
- 1. 中国移动通信集团江苏有限公司,江苏 南京 210000
- 折叠
摘要
该文首先概述了机器学习算法的基本原理和应用场景.然后以用户行为分析为重点,详细介绍了如何利用机器学习算法对移动通信核心网中的用户行为进行建模和分析.在此基础上,提出了实时优化与响应策略,根据用户行为模型进行动态的网络优化,并采用多种分析和评估指标对实验结果进行衡量.实验结果表明,基于机器学习的用户行为分析和优化调度策略可以显著提高移动通信核心网的网络性能,如提升用户体验感知、提高网络资源使用效率.
Abstract
Firstly,the basic principles and application scenarios of machine learning algorithms are outlined.Next,with a focus on user behavior analysis,a detailed introduction was given on how to use machine learning algorithms to model and analyze user behavior in the mobile communication core network.On this basis,real-time optimization and response strategies were proposed to dynamically optimize the network based on user behavior models.Multiple analysis and evaluation indicators are used to measure the experimental results.The experimental results show that user behavior analysis and optimization scheduling strategies based on machine learning can significantly improve the network performance of mobile communication core networks,such as enhancing user experience perception and improving network resource utilization efficiency.
关键词
移动通信/机器学习/用户行为Key words
mobile communication/machine learning/user behavior引用本文复制引用
出版年
2024
NETL
NSTL
万方数据