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- W2149490664 abstract "Because of overtting and the improvement of generalization capability (GC) available in the construction of forecasting models using articial neural network (ANN), a new method is proposed for model establishment by means of making a low-dimension ANN learning matrix through principal component analysis (PCA). The results show that the PCA is able to construct an ANN model without the need of nding an optimal structure with the appropriate number of hidden-layer nodes, thus avoids overtting by condensing forecasting information, reducing dimension and removing noise, and GC is greatly raised compared to the traditional ANN and stepwise regression techniques for model establishment." @default.
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- W2149490664 date "2004-01-01" @default.
- W2149490664 modified "2023-09-26" @default.
- W2149490664 title "Study on the Overtting of the Articial Neural Network Forecasting Model" @default.
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