User Behavior Analysis and Optimization Based on Machine Learning in Mobile Communication Core Network
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.
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