Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108579
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dc.contributorDepartment of Building and Real Estate-
dc.creatorSaka, A-
dc.creatorTaiwo, R-
dc.creatorSaka, N-
dc.creatorSalami, BA-
dc.creatorAjayi, S-
dc.creatorAkande, K-
dc.creatorKazemi, H-
dc.date.accessioned2024-08-19T01:59:12Z-
dc.date.available2024-08-19T01:59:12Z-
dc.identifier.urihttp://hdl.handle.net/10397/108579-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.rights© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Saka, A., Taiwo, R., Saka, N., Salami, B. A., Ajayi, S., Akande, K., & Kazemi, H. (2024). GPT models in construction industry: Opportunities, limitations, and a use case validation. Developments in the Built Environment, 17, 100300 is available at https://doi.org/10.1016/j.dibe.2023.100300.en_US
dc.subjectArtificial intelligenceen_US
dc.subjectChatGPTen_US
dc.subjectGenerative AIen_US
dc.subjectGPTen_US
dc.subjectLLMsen_US
dc.titleGPT models in construction industry : opportunities, limitations, and a use case validationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume17-
dc.identifier.doi10.1016/j.dibe.2023.100300-
dcterms.abstractLarge Language Models (LLMs) trained on large data sets came into prominence in 2018 after Google introduced BERT. Subsequently, different LLMs such as GPT models from OpenAI have been released. These models perform well on diverse tasks and have been gaining widespread applications in fields such as business and education. However, little is known about the opportunities and challenges of using LLMs in the construction industry. Thus, this study aims to assess GPT models in the construction industry. A critical review, expert discussion and case study validation are employed to achieve the study's objectives. The findings revealed opportunities for GPT models throughout the project lifecycle. The challenges of leveraging GPT models are highlighted and a use case prototype is developed for materials selection and optimization. The findings of the study would be of benefit to researchers, practitioners and stakeholders, as it presents research vistas for LLMs in the construction industry.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationDevelopments in the built environment, Mar. 2024, v. 17, 100300-
dcterms.isPartOfDevelopments in the built environment-
dcterms.issued2024-03-
dc.identifier.scopus2-s2.0-85180528081-
dc.identifier.eissn2666-1659-
dc.identifier.artn100300-
dc.description.validate202408 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextLeeds Beckett Universityen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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