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An instruction fine-tuning and retrieval-augmented generation framework for intelligent defect diagnosis and maintenance decision support in high-speed railway turnouts

Yi Wang Orcid Logo, Xiaopei Cai, Bin Cui, Xueyang Tang, Clare Wood Orcid Logo, Yue Hou Orcid Logo

Computer-Aided Civil and Infrastructure Engineering, Volume: 49, Start page: 100098

Swansea University Authors: Clare Wood Orcid Logo, Yue Hou Orcid Logo

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DOI (Published version): 10.1016/j.cacaie.2026.100098

Published in: Computer-Aided Civil and Infrastructure Engineering
ISSN: 1093-9687
Published: Elsevier BV 2026
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URI: https://cronfa.swan.ac.uk/Record/cronfa71989
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spelling 2026-05-28T14:27:14.3260392 v2 71989 2026-05-28 An instruction fine-tuning and retrieval-augmented generation framework for intelligent defect diagnosis and maintenance decision support in high-speed railway turnouts 97bede20cc14db118af8abfbb687e895 0000-0003-0001-0121 Clare Wood Clare Wood true false 92bf566c65343cb3ee04ad963eacf31b 0000-0002-4334-2620 Yue Hou Yue Hou true false 2026-05-28 ACEM Journal Article Computer-Aided Civil and Infrastructure Engineering 49 100098 Elsevier BV 1093-9687 1 9 2026 2026-09-01 10.1016/j.cacaie.2026.100098 https://doi.org/10.1016/j.cacaie.2026.100098 COLLEGE NANME Aerospace Civil Electrical and Mechanical Engineering COLLEGE CODE ACEM Swansea University 2026-05-28T14:27:14.3260392 2026-05-28T14:21:20.9476820 Yi Wang 0009-0005-0816-8152 1 Xiaopei Cai 2 Bin Cui 3 Xueyang Tang 4 Clare Wood 0000-0003-0001-0121 5 Yue Hou 0000-0002-4334-2620 6
title An instruction fine-tuning and retrieval-augmented generation framework for intelligent defect diagnosis and maintenance decision support in high-speed railway turnouts
spellingShingle An instruction fine-tuning and retrieval-augmented generation framework for intelligent defect diagnosis and maintenance decision support in high-speed railway turnouts
Clare Wood
Yue Hou
title_short An instruction fine-tuning and retrieval-augmented generation framework for intelligent defect diagnosis and maintenance decision support in high-speed railway turnouts
title_full An instruction fine-tuning and retrieval-augmented generation framework for intelligent defect diagnosis and maintenance decision support in high-speed railway turnouts
title_fullStr An instruction fine-tuning and retrieval-augmented generation framework for intelligent defect diagnosis and maintenance decision support in high-speed railway turnouts
title_full_unstemmed An instruction fine-tuning and retrieval-augmented generation framework for intelligent defect diagnosis and maintenance decision support in high-speed railway turnouts
title_sort An instruction fine-tuning and retrieval-augmented generation framework for intelligent defect diagnosis and maintenance decision support in high-speed railway turnouts
author_id_str_mv 97bede20cc14db118af8abfbb687e895
92bf566c65343cb3ee04ad963eacf31b
author_id_fullname_str_mv 97bede20cc14db118af8abfbb687e895_***_Clare Wood
92bf566c65343cb3ee04ad963eacf31b_***_Yue Hou
author Clare Wood
Yue Hou
author2 Yi Wang
Xiaopei Cai
Bin Cui
Xueyang Tang
Clare Wood
Yue Hou
format Journal article
container_title Computer-Aided Civil and Infrastructure Engineering
container_volume 49
container_start_page 100098
publishDate 2026
institution Swansea University
issn 1093-9687
doi_str_mv 10.1016/j.cacaie.2026.100098
publisher Elsevier BV
url https://doi.org/10.1016/j.cacaie.2026.100098
document_store_str 0
active_str 0
published_date 2026-09-01T17:21:00Z
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score 11.106612

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