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In the paper, a regularized correntropy criterion (RCC) for radial basis function neural network (RBFNN) is proposed. In RCC, the Gaussian kernel function is used to replace the Eculidean norm of the sum-squared-error (SSE) criterion. Replacing SSE by RCC can improve the anti-noise ability of RBFNN. Moreover, the optimal weights and the optimal bias terms can be iteratively obtained by the half-quadratic...
In short term load forecasting using Neural Networks, when the training data is contaminated with high noise, this noise is mapped into network's weights, and causes increasing of forecasting error. This forecasting error make us apply some methods to increase accuracy in neural net. In this paper, load forecasting of such power systems is done based on employing two methods: Pruning algorithm and...
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