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Case-based reasoning approach for decision-making in building retrofit: A review

Li, Y, Du, H and Kumaraswamy, SB (2023) Case-based reasoning approach for decision-making in building retrofit: A review. Building and Environment, 248. p. 111030. ISSN 0360-1323

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The rapid development of computer science has brought inspirations to building retrofit. Artificial intelligence (AI) provides more possibilities in decision-making for building retrofit, could be regarded as an alternative strategy compared to the abundant research time spent in the early decision-making stage of traditional retrofit approaches. This paper reviews the application of the statistic algorithm and AI approach, including CBR, in building retrofit decision-making, and the essential process of CBR, such as workflow, similarity degree calculation method, weight factors correction manner, and input or output content using building design to provide a synthetic overview of CBR utilisation in the building retrofit realm. Among those different models, Case-Based Reasoning (CBR) is valuable in providing references and avoiding possible failures, which is a promising approach for building retrofit. Yet, current research mainly focused on its utilisation to solve specific issues. There is still a lack of systematically summarised research on Case-Based Reasoning solution. Therefore, this study analyses the methods used for CBR approach in the field of building retrofit decision-making process, aiming to find the characteristics of internal commonness. It concludes that CBR has two significant impact factors: similarity attribute type and similarity calculation manner, which determines the judgement process. The results show that the CBR solution has great application potential in further building retrofit design.

Item Type: Article
Uncontrolled Keywords: 0502 Environmental Science and Management; 1201 Architecture; 1202 Building; Building & Construction
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TH Building construction
Divisions: Civil Engineering & Built Environment
Publisher: Elsevier
SWORD Depositor: A Symplectic
Date Deposited: 30 Nov 2023 14:29
Last Modified: 30 Nov 2023 14:30
DOI or ID number: 10.1016/j.buildenv.2023.111030
URI: https://researchonline.ljmu.ac.uk/id/eprint/21991
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