Multiresolution-based BiLinear recurrent neural network

A Multiresolution-based BiLinear Recurrent Neural Network (MBLRNN) is proposed in this paper. The proposed M-BLRNN is based on the BLRNN that has been proven to have robust abilities in modeling and predicting time series. The learning process is further improved by using a multiresolution-based learning algorithm for training the BLRNN so as to make it more robust for long-term prediction of the time series. The proposed M-BLRNN is applied to long-term prediction of network traffic. Experiments and results on Ethernet network traffic data show that the proposed M-BLRNN outperforms both the traditional Multi-Layer Perceptron Type Neural Network (MLPNN) and the BLRNN in terms of the normalized mean square error (NMSE).