A NETWORK TRAFFIC HYBRID PREDICTION MODEL OPTIMIZED BY IMPROVED HARMONY SEARCH ALGORITHM

Z. Tian ； S. Li ； Y. Wang ； X. Wang

《Neural Network World》 25卷6期 (2015/12) Pp. 669-686

https://doi.org/10.14311/NNW.2015.25.034

摘要

The telecommunication and Ethernet traffic prediction problem is studied. Network traffic prediction is an important problem of telecommunication and Ethernet congestion control and network management. In order to improve network traffic prediction accuracy, a network traffic hybrid prediction model was proposed by using the advantages of grey model and Elman neural network, grey model and Elman neural network predictive values were independently obtained, the different weight coefficients of two prediction models were given. In terms of weight coefficients optimization, an improved harmony search algorithm with better convergence speed and accuracy was proposed, the optimal weight coefficients of network traffic hybrid prediction model were determined through this algorithm, two prediction models results were multiplied by the weight coefficients to obtain the final prediction value. The network traffic sample data from an actual telecommunication network was collected as simulation object. The simulation results verified that the proposed network traffic hybrid prediction model based on improved harmony search algorithm has higher prediction accuracy.

關鍵字

network traffic ； grey model ； Elman neural network ； prediction ； improved harmony search