%A Fang GUO,Lei CHEN,Ziwen YANG %T Real-time traffic prediction based on MGU for large-scale IP backbone networks %0 Journal Article %D 2019 %J Journal of Shandong University(Engineering Science) %R 10.6040/j.issn.1672-3961.0.2018.342 %P 88-95 %V 49 %N 2 %U {http://gxbwk.njournal.sdu.edu.cn/CN/abstract/article_1814.shtml} %8 2019-04-20 %X

In order to overcome the shortcomings of long short-term memory (LSTM) computing cost, a real-time traffic prediction method based on minimum gated unit (MGU) for large-scale IP backbone networks was proposed. The experimental results showed that compared with the LSTM-based traffic prediction method, the proposed method achieved fairly or even better traffic prediction performance with less model training time, meanwhile it outperformed the most advanced feed forward neural network (FFNN), LSTM and gated recurrent unit(GRU) in terms of prediction accuracy and real-time performance.