基于LSTM算法的无线网络流量预测研究

Traffic Prediction of MobileCommunication Network Based on LSTM Algorithm

提出了一个基于改进型长短期记忆循环神经网络的无线网络流量预测模型。在模型训练结构方面进行了改进,通过对参数元素进行权重赋值,提高了模型运行效率。在对实际网络流量预测的实验中,文章所提出的算法在预测精度和算法训练速度与经典算法相比有了较好的改善和进步,满足了无线网络流量预测需求,有良好的应用前景。

A traffic prediction model of wireless network based on improved long-short memory cyclic neural network is proposed.The model training structure is improved,and the weight of parameter elements is assigned to improve the efficiency of the model.In the experiment of actual network traffic prediction,the algorithm proposed in this paper has a better improvement and progress in the prediction accuracy and algorithm training speed compared with the classical algorithm,which meets the demand of wireless network traffic prediction and has a good application prospect.