The Training Selection Method for Short-Term Prediction Electricity Loads with Criteria of Informativeness and Compactness

Abstract

The paper considers the method of forming a training sample for intelligent methods of predicting electricity loads based on artificial neural networks. The training sample is formed taking into account the criteria of informativeness and compactness. It is shown how much the accuracy of the forecast can be increased with the approach used.