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Bayesian neural networks for electric load forecasting

The authors apply Bayesian neural networks to electric load forecasting with real data from some Brazilian power companies. The Bayesian methods used are the Gaussian approximation and the Markov chain Monte Carlo (MCMC) methods. The results obtained with these methods are favourably compared to backpropagation and some standard statistical techniques like Box & Jenkins and Holt-Winters.