TY - GEN
T1 - Intelligent forecasting system based on grey model and neural network
AU - Yang, Shih Hung
AU - Chen, Yon-Ping
PY - 2009
Y1 - 2009
N2 - This paper presents the design issues of two intelligent forecasting systems, feedforward-neural-networkaided grey model (FNAGM) and Elman-network-aided grey model (ENAGM). Both he FNAGM and ENAGM combine a first-order single variable grey model (GM(1,1)) and a neural network (NN). The GM(1,1) is adopted to predict signal, and the feedforward NN and the Elman network in the FNAGM and ENAGM respectively are used to learn the prediction error of the GM(1,1). Simulation results demonstrate that the intelligent forecasting systems with on-line learning can improve the prediction of the GM(1,1) and can be implemented in real-time prediction.
AB - This paper presents the design issues of two intelligent forecasting systems, feedforward-neural-networkaided grey model (FNAGM) and Elman-network-aided grey model (ENAGM). Both he FNAGM and ENAGM combine a first-order single variable grey model (GM(1,1)) and a neural network (NN). The GM(1,1) is adopted to predict signal, and the feedforward NN and the Elman network in the FNAGM and ENAGM respectively are used to learn the prediction error of the GM(1,1). Simulation results demonstrate that the intelligent forecasting systems with on-line learning can improve the prediction of the GM(1,1) and can be implemented in real-time prediction.
UR - http://www.scopus.com/inward/record.url?scp=70350459662&partnerID=8YFLogxK
U2 - 10.1109/AIM.2009.5229929
DO - 10.1109/AIM.2009.5229929
M3 - Conference contribution
AN - SCOPUS:70350459662
SN - 9781424428533
T3 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
SP - 699
EP - 704
BT - 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2009
T2 - 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2009
Y2 - 14 July 2009 through 17 July 2009
ER -