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Predicting System loads with Artificial Neural Networks : Method and Result from "the Great Energy Predictor Shootout"
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1994
Year
EngineeringMachine LearningMultilayer PerceptronLoad ControlData ScienceSystems EngineeringPrediction CompetitionEnergy Demand ManagementPredictive AnalyticsDemand ForecastingEnergy ForecastingComputer ScienceForecastingEnergy PredictionPredictive LearningIntelligent ForecastingEnergy ModelingArtificial Neural NetworksSmart GridEnergy ManagementUtility Loads
We devise a feed-forward Artificial Neural Network (ANN) procedure for predicting utility loads and present the resulting predictions for two test problems given by ``The Great Energy Predictor Shootout - The First Building Data Analysis and Prediction Competition''. Key ingredients in our approach are a method ($\delta$ -test) for determiningrelevant inputs and the Multilayer Perceptron. These methods are briefly reviewed together with comments on alternative schemes like fitting to polynomials and the use of recurrent networks.