<div class="csl-bib-body">
<div class="csl-entry">Orehounig, K. (2024, November 29). <i>AI for Decarbonizing Buildings: Transformation of the Current Building Stock to Reach Climate Neutrality</i> [Conference Presentation]. Symposium on AI-supported Architecture: Shaping Spaces for Health, Education, and Sustainability in Vienna, Wien, Austria.</div>
</div>
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/205198
-
dc.description
Net Zero Strategies for Buildings
The role of machine learning?
Modelling of the Swiss building stock
Analyze building data with ML
Energy consumption before and after
Pathways of reduction
Effect of retrofitting measures
Optimize buildings' energy performance
Optimal retrofitting strategies for buildings
Optimal retrofitting strategies for buildings –
an ML based approach
Machine learning-based surrogate model:
Structural Breakdown
Machine learning-based surrogate model:
Prediction performance
Optimal retrofitting strategies for buildings –
applied to Geneva
Optimize the control of
buildings
Data-predictive control of buildings
Physical models as digital twins
Self-learning data-driven models
-
dc.description.sponsorship
Swiss Federal office for Energy
-
dc.language.iso
en
-
dc.subject
Artificial Intelligence
en
dc.subject
Building Retrofit
en
dc.subject
Decarbonizing Buildings
en
dc.title
AI for Decarbonizing Buildings: Transformation of the Current Building Stock to Reach Climate Neutrality
en
dc.type
Presentation
en
dc.type
Vortrag
de
dc.relation.grantno
SI/502495-01
-
dc.type.category
Conference Presentation
-
tuw.publication.invited
invited
-
tuw.project.title
Nachhaltiges Wohlbefinden für den Einzelnen und die Gemeinschaft in der Energiewende
-
tuw.researchTopic.id
E1
-
tuw.researchTopic.id
E5
-
tuw.researchTopic.id
C6
-
tuw.researchTopic.name
Energy Active Buildings, Settlements and Spatial Infrastructures
-
tuw.researchTopic.name
Efficient Utilisation of Material Resources
-
tuw.researchTopic.name
Modeling and Simulation
-
tuw.researchTopic.value
30
-
tuw.researchTopic.value
30
-
tuw.researchTopic.value
40
-
tuw.publication.orgunit
E259-03 - Forschungsbereich Bauphysik und Bauökologie
-
tuw.author.orcid
0000-0001-6491-7641
-
tuw.event.name
Symposium on AI-supported Architecture: Shaping Spaces for Health, Education, and Sustainability in Vienna
en
tuw.event.startdate
29-11-2024
-
tuw.event.enddate
29-11-2024
-
tuw.event.online
On Site
-
tuw.event.type
Event for scientific audience
-
tuw.event.place
Wien
-
tuw.event.country
AT
-
tuw.event.institution
Center for Artificial Intelligence and Machine Learning (CAIML) & Department of Digital Architecture and Planning / TU Wien
