A Novel Neural Computing Model for Fast Predicting Network Traffic
Qi Liu, Weidong Cai, Jian Shen, Zhangjie Fu, Nigel Linge · Journal of Computational and Theoretical Nanoscience · 2015
Currently existing web traffic prediction models have the shortages of low accuracy, low stability and slow training speed. Aiming at such problems, this paper proposes a new model to predict the network traffic called MRERPM (MapReduce-based ELM Regression Prediction Model). In this prediction model, Extreme Learning Machine is used to accelerate the training speed and improve the accuracy of prediction. Moreover, a distributed cluster is established based on Apache Hadoop to furtherly improve the processing capacity. Experiment results show that MRERM has a large improvement over training speed compared with other models based on K-ELM or SVR, but not at the cost of accuracy.