2018 · 15 citations · 11 references
ComputingComputer ScienceData ScienceForecastingMachine LearningTime Series AnalysisDeep LearningLoad AnalysisLoad ForecastingSupport Vector MachinesTime Series ForecastingTime Series PredictionDeep Learning-based ForecastingElectric Load ForecastingPeak Load DemandPeak Load ForecastingShort-term Load ForecastingSupport Vector Machine ClassificationTrainingTraining Sample Selection
In this paper, a short-term load forecasting model based on load type recognition is established. According to the characteristics of electric power load, the load data can be divided into three types: peak load, valley load and normal load. During the forecasting process, the support vector machine recognition model is used to determine load type on the predicted time point. After then, load samples of the same type are selected as the training sample to establish deep learning forecasting model. Finally, the trained model is applied to forecasting the load value. The experimental comparison shows that its prediction accuracy is higher than that of other models.
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Ensemble deep learning for regression and time series forecasting
Xueheng Qiu, Le Zhang, Ye Ren et al. · 2014 · 368 citations