In order to satisfy users'' high-quality experience and save resources, it is necessary to predict the traffic data of mobile communication base station, so that mobile communication base station
This paper studies the prediction models for electrical load data of 5G base stations. Firstly, the characteristics of the CEEMDAN algorithm are introduced, and the
The Elman neural network is utilized in this study to anticipate mobile base station traffic. The Elman neural network has reverse adjustment transferring from the output layer to
By predicting the traffic load on base stations, network optimization techniques can be applied to decrease energy consumption. This research explores different machine learning
In order to reduce and reduce the error of predicting network flow data, a neural network algorithm prediction model based on machine deep learning, long and short memory network flow
In the domain of 5G network management, accurately predicting traffic volumes at base stations remains a critical yet challenging endeavor, primarily due to the complexities
Therefore, to improve the learning efficiency and prediction accuracy, this paper presents a new method that first uses decomposition and reconstruction of wavelet transform to preprocess
PDF | To ensure the safe and stable operation of 5G base stations, it is essential to accurately predict their power load.
Abstract: Communication base station traffic prediction can help network service providers predict the peak hours of network traffic, so as to carry out network expansion and load balancing in
In emergencies (such as natural disasters, terrorist attacks, etc.), 5G base station traffic prediction and load balancing can ensure the stability and availability of communication
By predicting the traffic load on base stations, network optimization techniques can be applied to decrease energy consumption.
PDF | To ensure the safe and stable operation of 5G base stations, it is essential to accurately predict their power load.
This paper studies the prediction models for electrical load
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