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This paper proposes a hybrid negative correlation learning in which each individual neural network in an neural network ensemble would either learn a data point by negative correlation learning or learn to be different to the neural network ensemble. The implementation is through randomly splitting the training set into two subsets for each individual neural network in learning. On one subset of the...
A new method, called OSR-BP neural network, for long-term runoff prediction is put forward in this thesis. In order to eliminate input multi-collinearity and phenomenon of overfitting of the neural network, optimal subset regression (OSR) and BackPropagation(BP) neural network is coupled to an integrated, meanwhile, the training and testing error is comprehensively considered to determine the best...
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