Machine Learning-Based Framework to Predict Single and Multiple Daylighting Simulation Outputs Using Neural Networks
| dc.creator | Labib, Rania | |
| dc.date.accessioned | 2022-09-19T14:45:29Z | |
| dc.date.available | 2022-09-19T14:45:29Z | |
| dc.date.issued | 2021-09 | |
| dc.identifier.uri | https://hdl.handle.net/1969.1/196863 | |
| dc.publisher | The17th IBPSA Conference, Bruges, Belgium | en_US |
| dc.subject | Machine Learning for Daylighting | en_US |
| dc.subject | Building Performance Simulations | en_US |
| dc.subject | BPS | en_US |
| dc.subject | Artifical Intelligence | en_US |
| dc.subject | Daylighting | en_US |
| dc.subject | Deep Learning | en_US |
| dc.subject | Neural Network | en_US |
| dc.subject | Parametric Daylighting | en_US |
| dc.subject | High Performance Computing | en_US |
| dc.subject | IBPSA | en_US |
| dc.subject | Daylight Autonomy | en_US |
| dc.title | Machine Learning-Based Framework to Predict Single and Multiple Daylighting Simulation Outputs Using Neural Networks | en_US |
| dc.type | Article | en_US |
| local.department | Architecture | en_US |
| dc.identifier.doi | 10.26868/25222708.2021.30261 |