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Energy-efficient re...
Energy-efficient retrofitting with incomplete building information : a data-driven approach
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- Feng, Kailun (författare)
- Umeå universitet,Institutionen för tillämpad fysik och elektronik
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- Lu, Weizhuo, Professor, 1974- (författare)
- Umeå universitet,Institutionen för tillämpad fysik och elektronik
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- Penaka, Santhan Reddy (författare)
- Umeå universitet,Institutionen för tillämpad fysik och elektronik
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- Eklund, Erik (författare)
- Umeå Municipality, Sweden
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- Andersson, Staffan, 1952- (författare)
- Umeå universitet,Institutionen för tillämpad fysik och elektronik
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- Olofsson, Thomas, 1968- (författare)
- Umeå universitet,Institutionen för tillämpad fysik och elektronik
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(creator_code:org_t)
- 2022-08-31
- 2022
- Engelska.
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Ingår i: E3S web of conferences. - : EDP Sciences.
- Relaterad länk:
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https://doi.org/10.1...
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https://umu.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- The high-performance insulations and energy-efficient HVAC have been widely employed as energy-efficient retrofitting for building renovation. Building performance simulation (BPS) based on physical models is a popular method to estimate expected energy savings for building retrofitting. However, many buildings, especially the older building constructed several decades ago, do not have full access to complete information for a BPS method. To address this challenge, this paper proposes a data-driven approach to support the decision-making of building retrofitting under incomplete information. The data-driven approach is constructed by integrating backpropagation neural networks (BRBNN), fuzzy C-means clustering (FCM), principal component analysis (PCA), and trimmed scores regression (TSR). It is motivated by the available big data sources from real-life building performance datasets to directly model the retrofitting performances without generally missing information, and simultaneously impute the case-specific incomplete information. This empirical study is conducted on real-life buildings in Sweden. The result indicates that the approach can model the performance ranges of energy-efficient retrofitting for family houses with more than 90% confidence. The developed approach provides a tool to predict the performance of individual buildings from different retrofitting measures, enabling supportive decision-making for building owners with inaccessible complete building information, to compare alternative retrofitting measures.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Husbyggnad (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Building Technologies (hsv//eng)
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)