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- W2102748725 abstract "This paper presents the design issues of two intelligent forecasting systems, feedforward-neural-network-aided 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." @default.
- W2102748725 created "2016-06-24" @default.
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- W2102748725 date "2009-07-01" @default.
- W2102748725 modified "2023-09-26" @default.
- W2102748725 title "Intelligent forecasting system based on grey model and neural network" @default.
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- W2102748725 doi "https://doi.org/10.1109/aim.2009.5229929" @default.
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