Regularization of neural networks for improved load forecasting in the power system
نویسنده
چکیده
The paper presents the regularization procedure for the neural network reduction to obtain the best results of load forecasting in the power system. The OBD pruning method will be applied in the solution. The numerical experiments have been concentrated on the prognosis of the load in the power system. Two kinds of experiments will be described: 24-hour forecast and the forecast of the daily mean of the load. It will be shown that application of the regularization of the neural network employed for prediction, will result in significant improvement of the forecasting accuracy.
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