Development of a Machine-Learning Framework for Overall Daylight and Visual Comfort Assessment in Early Design Stages

Application of machine learning methods as an alternative for building simulation software has been progressive in recent years. This research is mainly focused on the assessment of machine learning algorithms in prediction of daylight and visual comfort metrics in the early design stages and provid...

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Autores principales:	Hanieh Nourkojouri, Nastaran Seyed Shafavi, Mohammad Tahsildoost, Zahra Sadat Zomorodian
Formato:	article
Lenguaje:	EN
Publicado:	SolarLits 2021
Materias:	artificial neural networks machine learning daylight assessment visual comfort Details in building design and construction. Including walls, roofs TH2025-3000
Acceso en línea:	https://doaj.org/article/be97f02be2704d5aa130154e4b7a94ee
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Development of a Machine-Learning Framework for Overall Daylight and Visual Comfort Assessment in Early Design Stages

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