Training sample dimensions impact on artificial neural network optimal structure

The paper addresses the problem of electric load forecasting, using artificial neural networks mathematical apparatus, subject to error minimization on the long forecasting interval. Balanced artificial neural network architecture gives the possibility to maintain small deviation between forecasted and real values simultaneously with constrained squared error variation maintenance. Proposed methodology was verified using real data.