Abstract
Abstract The most commonly used Box-Jenkins approach for forecasting purposes has been modified to account for seasonality, employing a powerful orthogonal transform called the Walsh transform. The non-stationarity has been identified and after removing trends, the series is divided into segments of one period length. The segments have been transformed and the coefficients have then been time series modelled. A forecast has been made for monthly energy demand for 1 year and the result is compared with actual demand.
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