A data-driven energy performance gap prediction model using machine learning

Derya Yılmaz, Ali Murat Tanyer and İrem Dikmen Toker

Renewable and Sustainable Energy Reviews, 2023, vol. 181, issue C

Abstract: The energy performance gap is a significant obstacle to the realization of ambitions to mitigate the environmental impact of buildings. Although extensive research has been conducted on the causes, minimization, or the quantifying of the energy performance gap in buildings, comparatively minimal work has been done on raising decision-makers awareness of a potential gap.

Keywords: Algorithm; Building; Classification; Energy performance gap; Machine learning; Risk identification (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1016/j.rser.2023.113318

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