Machine learning informed knowledge driven framework supporting holistic bridge maintenance

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dc.contributor.authorJiang, Yalien
dc.contributor.authorYang, Gangen
dc.contributor.authorLi, Haijiangen
dc.contributor.authorZhao, Kaien
dc.contributor.authorZhang, Tianen
dc.date.accessioned2024-11-26T15:19:44Z
dc.date.available2024-11-26T15:19:44Z
dc.date.issued2021en
dc.description.abstractBridge maintenance is a complex task, which demands a wide spectrum of factors to achieve multi-objectives, multi-criteria optimum decisions. Physics-informed analysis can simulate complex and closely coupled problems, e.g., bridge structural analysis. However, it cannot account for some loosely coupled discrete factors, which complementarily could be addressed by ontological based semantic inference. This paper presents an overarching machine learning (ML) informed knowledge driven framework, which can enhance existing and static knowledge base via dynamically linking to real-time ML information for bridge structural safety as the governing consideration, to make accurate and holistic maintenance decisions. The framework includes semantic modelling, ML based numerical modelling and the Web OWL based reasoning mechanism for integration. The approach could contribute to some fundamental mindset changes towardsmaintenance decision making.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationJiang, Y., Yang, G., Li, H., Zhao, K. and Zhang, T. (2021) 'Machine learning informed knowledge driven framework supporting holistic bridge maintenance', 28th EG-ICE International Workshop, 30 June - 2 July 2021, Hybrid.en
dc.identifier.endpage10en
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/16678
dc.language.isoenen
dc.relation.ispartof28th EG-ICE International Workshop, 30 June - 2 July 2021.en
dc.rights© 2021, the Authors.en
dc.subjectBridge maintenanceen
dc.subjectKnowledge engineeringen
dc.subjectOntologyen
dc.subjectMachine learningen
dc.titleMachine learning informed knowledge driven framework supporting holistic bridge maintenanceen
dc.typeConference itemen
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