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| Creator | Title | Description | Subject | Date | ||
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Rahman, Aowabin | Deep recurrent neural networks for building energy prediction | This poster illustrates the development of a deep recurrent neural network (RNN) model using long-short-term memory (LSTM) cells to predict energy consumption in buildings at one-hour time resolution over medium-to-long term time horizons ( greater than or equal to 1 week). | Machine learning; Energy; Building energy modeling; Deep learning; Recurrent neural networks; Prediction | 2017-01-13 |
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Didier, Richard C. | Linking microclimate and energy use with a low cost wall mounted measurement system | Urban microclimate plays a critical role in overall urban energy demand and efficiency. At the building scale, energy use and internal conditions are directly impacted by local microclimate. The direct link between building energy use and local microclimate is through building envelope heat fluxes. ... | Microclimate; Energy; Temperature; Humidity; Arduino; EnergyPlus | 2016-06 |
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