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Knowledge and Information Systems

, Volume 19, Issue 2, pp 235–248 | Cite as

Multiresolution-based bilinear recurrent neural network

  • Dong-Chul ParkEmail author
Regular Paper

Abstract

A multiresolution-based bilinear recurrent neural network (MBLRNN) is proposed in this paper. The proposed MBLRNN is based on the BLRNN that has 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 the prediction of time series data. The proposed MBLRNN is applied to the problems of network traffic prediction and electric load forecasting. Experiments and results on both practical problems show that the proposed MBLRNN outperforms both the traditional multilayer perceptron type neural network (MLPNN) and the BLRNN in the prediction accuracy.

Keywords

Wavelet transform Recurrent neural network Time series prediction Network traffic Load forecasting 

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Copyright information

© Springer-Verlag London Limited 2008

Authors and Affiliations

  1. 1.ICRL, Department of Information EngineeringMyong Ji UniversityYong InRepublic of Korea

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