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BUTTER Empirical Deep Learning Dataset
The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four le...
Tripp, C. et al National Renewable Energy Laboratory
May 20, 2022
4 Resources
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4 Resources
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Curated Modeled Fault Data Set
The curated fault model simulation data set consists of tagged and fully-described time series representing simulated faults for the AFDD test building (ORNLs Flexible Research Platform (FRP)), including baseline performance, faulty performance, and corresponding energy impact. A ...
Kim, J. and Leach, M. National Renewable Energy Laboratory
Jun 24, 2019
7 Resources
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7 Resources
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National Renewable Energy Laboratory/Habitat for Humanity Zero Energy Home: A Cold Climate Case Study for Affordable Zero Energy Homes
The design of this 1,280-square-foot, three-bedroom Habitat for Humanity of Metro Denver zero energy home carefully combines envelope efficiency, efficient equipment, appliances and lighting, and passive and active solar features to reach the zero energy goal. The home was designe...
Norton, P. et al National Renewable Energy Laboratory
Jul 21, 2016
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4 Resources
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Visual Impact Assessment of the Existing Land-based Wind Turbine Fleet of the Contiguous United States
This data submission contains GIS raster datasets mapping the visual impacts of the land-based wind turbine fleet in the Contiguous United States (CONUS). Two datasets are included, each presenting a different quantification of visual impacts:
1. Cumulative visual magnitude, meas...
Gleason, M. et al National Renewable Energy Lab
Mar 19, 2024
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3 Resources
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