Traffic Prediction of 5G Communication Network Based on Improved BPNN
In order to improve the accuracy of 5G network traffic prediction results,a 5G communication network traffic prediction method based on improved Back Propagation Neural Network(BPNN)is proposed.Arithmetic Optimization Algorithm(AOA)algorithm is used to optimize the weight coefficients and thresholds of BPNN,and a 5G communication network traffic prediction model based on AOA-BPNN is established.Simulation analysis is conducted using network communication traffic monitoring data from a certain 5G base station,and the prediction results are compared with other methods.The results show that the average relative error and root mean square error of the AOA-BPNN model proposed in this paper were 4.25%and 0.522 GB,the prediction accuracy is higher than other methods,verifying the practicality and superiority of the proposed method.
万方数据
维普
