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| Creator | Title | Description | Subject | Date | ||
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Bianchi, Carlo | Energy demands for commercial buildings with climate variability based on emission scenarios | The impacts of a changing climate are wide-ranging in both impact and scope. This paper investigates the effect that realistic climate variability would have on building energy demands in Salt Lake City, UT to inform planning for air quality impacts. Energy demand scenarios were derived using climat... | BEM; EnergyPlus; Emissions; Climate; Energy | 2017 |
| 2 |
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Rahman, Aowabin | Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks | This paper presents a recurrent neural network model to make medium-to-long term predictions, i.e. time horizon of ≥ 1 week, of electricity consumption profiles in commercial and residential buildings at one-hour resolution. Residential and commercial buildings are responsible for a significant fr... | Building Energy Modeling; Machine learning; Recurrent neural networks; Deep learning; Electric load prediction | 2017 |
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