Application Simulation of Generalized Neural Network in Data Traffic Prediction
In the traffic prediction of massive data,data are prone to defects,error or incomplete problems.And the generalized neural network has strong robustness and fault-tolerant ability for processing data.In this paper,data traffic prediction was taken as the research objective,and the characteristics of data traffic were analyzed to obtain the spatial characteristics corresponding to the spatial-temporal characteristics and spatial dimensions of data traffic.Mo-reover,the data flow that correlated the most with the tested network was selected as the input of the generalized neu-ral network.Finally,a model of predicting data flow was built based on the generalized neural network.In order to verify the application effect of generalized neural network,a comparative test was designed.The simulation results show that the generalized neural network is feasible in predicting data traffic,with lower prediction error of data traffic.