A Communication Network Traffic Prediction Model Based on Deep Learning
DOI:
https://doi.org/10.53469/ijomsr.2025.08(08).02Keywords:
Deep learning, Communication network, Traffic prediction, ModelingAbstract
With the rapid development of information technology, communication network traffic prediction has become one of the key technologies for optimizing network resource allocation and improving user experience. Traditional prediction methods are inadequate when facing large-scale, nonlinear, and high-dimensional communication network traffic data. Therefore, this article explores the use of deep learning technology to construct a communication network traffic prediction model in order to achieve more accurate prediction results. This article first summarizes the challenges of current communication network traffic prediction and the potential applications of deep learning technology. Then, it elaborates in detail on the design and implementation of a communication network traffic prediction model based on deep learning, and explores its key technologies and algorithms in depth. Finally, it looks forward to the potential optimization directions of the model.
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