articleTop 1% cited
Random Forest based hourly building energy prediction
Energy and Buildings · 2018 · Vol. 171 · pp. 11–25
Zeyu Wang(Guangzhou University)Yueren Wang✉(Microsoft (United States))Ruochen Zeng(University of Florida)Ravi Srinivasan(University of Florida)Sherry Ahrentzen(University of Florida)
Building Energy and Comfort OptimizationNoise Effects and ManagementEnergy Load and Power ForecastingRandom forestPredictive modellingSupport vector machineRegression analysisEnergy (signal processing)Computer scienceRegressionEfficient energy useEnvironmental scienceStatistics
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595
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References
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Machine Learning · 2000 · 2,926 citations
A decision tree method for building energy demand modeling
Energy and Buildings · 2010 · 605 citations
Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools
Energy and Buildings · 2012 · 758 citations
Applying support vector machines to predict building energy consumption in tropical region
Energy and Buildings · 2004 · 787 citations
A review on the prediction of building energy consumption
Renewable and Sustainable Energy Reviews · 2012 · 1,868 citations
User behavior in whole building simulation
Energy and Buildings · 2008 · 607 citations
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