besos: Building and energy simulation, optimization and surrogate modelling

dc.contributor.authorWestermann, Paul
dc.contributor.authorChristiaane, Theodor Victor
dc.contributor.authorBeckett, Will
dc.contributor.authorKovacs, Paul
dc.contributor.authorEvins, Ralph
dc.date.accessioned2025-09-09T23:00:42Z
dc.date.available2025-09-09T23:00:42Z
dc.date.issued2021
dc.description.abstractThe buildings sector is one of the largest contributors to CO2 emissions, comprising up to 33% of the global total (ürge-Vorsatz et al., 2007). Improved computational methods are needed to help design more energy-efficient buildings. The Python library besos along with its associated web-based platform BESOS help researchers and practitioners explore energy use in buildings more effectively. This is achieved by providing an easy way of integrating many disparate aspects of building modelling, district modelling, optimization and machine learning into one common library.
dc.description.reviewstatusReviewed
dc.description.scholarlevelFaculty
dc.identifier.citationWestermann, P. Christiaansem T.V. Beckett, W. Kovacs, P. Evins, R. (2021) besos: Building and energy simulation, optimization and surrogate modelling. The Journal of Open Source Software, 60, 2677. https://doi.org/10.21105/joss.02677
dc.identifier.urihttps://doi.org/10.21105/joss.02677
dc.identifier.urihttps://hdl.handle.net/1828/22739
dc.language.isoen
dc.publisherJournal of Open Source Software
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectEnergy in Cities
dc.subjectInstitute for Integrated Energy Systems (IESVic)
dc.subject.departmentDepartment of Civil Engineering
dc.titlebesos: Building and energy simulation, optimization and surrogate modelling
dc.typeArticle

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