Comparative Performance of Machine Learning Algorithms in the Prediction of Indoor Daylight Illuminances

Comparative Performance of Machine Learning Algorithms in the Prediction of Indoor Daylight Illuminances

The performance of machine learning (ML) algorithms depends on the nature of the problem at hand. ML-based modeling, therefore, should employ suitable algorithms where optimum results are desired. The purpose of the current study was to explore the potential applications of ML algorithms in modeling...

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Bibliographic Details
Main Authors: Jack Ngarambe, Amina Irakoze, Geun Young Yun, Gon Kim
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Sustainability
Subjects:
machine learning
daylighting performance
daylighting control
deep learning
decision trees
daylight forecasting
Online Access:https://www.mdpi.com/2071-1050/12/11/4471

Internet

https://www.mdpi.com/2071-1050/12/11/4471

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