Damitha K. Ranaweera

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A description and original application of a type of neural network, called the radial basis function network (RBFN), to the short -term system load forecasting (SLF) problem is presented. The predictive capability of the RBFN models and their ability to produce accurate measures that can be used to estimate confidence intervals for the short-term forecasts(More)
This paper presents a novel method to include the uncertainties or the weather-related input variables in neural network-based electric load forecasting models. The new method consists of traditionally trained neural networks and a set of equations to calculate the mean value and confidence intervals of the forecasted load. This method was tested for daily(More)
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