首页 | 本学科首页   官方微博 | 高级检索  
     


Multiresolution-based bilinear recurrent neural network
Authors:Dong-Chul Park
Affiliation:(1) ICRL, Department of Information Engineering, Myong Ji University, Yong In, 449-723, Republic of Korea
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.
Contact Information Dong-Chul ParkEmail: Email:
Keywords:Wavelet transform  Recurrent neural network  Time series prediction  Network traffic  Load forecasting
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号