Research on Short-term Load Forecasting of Power System Based on Deep Learning
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- Research on Short-term Load Forecasting of Power System Based on Deep Learning
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Conventional regression versus artificial neural network in short-term load forecasting
SpringSim '10: Proceedings of the 2010 Spring Simulation MulticonferenceIn order to short-term load forecasting (STLF), two different seasonal artificial neural networks (ANNs) are designed and compared with conventional regression. Furthermore designed ANNs are compared with each other in terms of model complexity, ...
Neural networks for pattern-based short-term load forecasting
In this work several univariate approaches for short-term load forecasting based on neural networks are proposed and compared. They include: multilayer perceptron, radial basis function neural network, generalized regression neural network, fuzzy ...
Short-term load forecasting using lifting scheme and ARIMA models
Research highlights Short-term load forecasting is achieved using a lifting scheme and autoregressive integrated moving average (ARIMA) models. Lifting scheme is embedded into the ARIMA models to enhance forecasting accuracy. The Coeflet 12 wavelet is ...
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Association for Computing Machinery
New York, NY, United States
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