articleTop 1% cited
Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks
Applied Energy · 2017 · Vol. 212 · pp. 372–385
Aowabin Rahman(University of Utah)Vivek Srikumar(University of Utah)Amanda D. Smith✉(University of Utah)
Building Energy and Comfort OptimizationEnergy Load and Power ForecastingImage and Signal Denoising MethodsElectricityArtificial neural networkConsumption (sociology)Recurrent neural networkTime horizonComputer sciencePredictive modellingEnergy consumptionDeep learningImputation (statistics)
Funding
- National Science Foundation
Citations
722
FWCI
46.92
field-weighted impact
References
33
Percentile
100%
vs. same field & year
Citations per year
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References
Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior
Energy · 2013 · 577 citations
A review on the prediction of building energy consumption
Renewable and Sustainable Energy Reviews · 2012 · 1,868 citations
Long Short-Term Memory
Neural Computation · 1997 · 95,078 citations
Electric load forecasting using an artificial neural network
IEEE Transactions on Power Systems · 1991 · 1,422 citations
A short-term building cooling load prediction method using deep learning algorithms
Applied Energy · 2017 · 660 citations
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