{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:54:07Z","timestamp":1781830447658,"version":"3.54.5"},"reference-count":72,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People's Republic of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003392","name":"Fujian Provincial Natural Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Advanced Engineering Informatics"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.aei.2026.104979","type":"journal-article","created":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T21:20:01Z","timestamp":1781817601000},"page":"104979","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["Deep learning surrogate-based differentiable optimisation inversion method for structural condition assessment of assembled slab girder bridges"],"prefix":"10.1016","volume":"76","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4227-8559","authenticated-orcid":false,"given":"Jing-Lin","family":"Xiao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu-Fei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian-Sheng","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.aei.2026.104979_b0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103564","article-title":"A semi-automated method for verification and reliability assessment of network-scale bridge asset data","volume":"68","author":"Hodge","year":"2025","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104979_b0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103373","article-title":"An efficient 2D-3D fusion method for bridge damage detection under complex backgrounds with imbalanced training data","volume":"65","author":"Zhang","year":"2025","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104979_b0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103766","article-title":"Multimodal information-driven intelligent damage detection framework for full components of highway prefabricated bridges","volume":"68","author":"Xu","year":"2025","journal-title":"Adv. Eng. Inf."},{"issue":"12","key":"10.1016\/j.aei.2026.104979_b0020","doi-asserted-by":"crossref","DOI":"10.1061\/(ASCE)BE.1943-5592.0001644","article-title":"Experimental study on shear behavior of a UHPC connection between adjacent precast prestressed concrete voided beams","volume":"25","author":"Jiang","year":"2020","journal-title":"J. Bridg. Eng."},{"key":"10.1016\/j.aei.2026.104979_b0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2024.119559","article-title":"Performance evaluation of existing reinforced concrete hollow-slab beams: Experiments and fibre beam element-based model updating","volume":"326","author":"Xiao","year":"2025","journal-title":"Eng. Struct."},{"key":"10.1016\/j.aei.2026.104979_b0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2025.120128","article-title":"Field tests and structural performance evaluation of existing reinforced concrete hollow slab beam bridges","volume":"333","author":"Xiao","year":"2025","journal-title":"Eng. Struct."},{"issue":"2","key":"10.1016\/j.aei.2026.104979_b0035","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1080\/10168664.2021.2022446","article-title":"Full-range experimental analysis of flexural performance of an existing PC hollow slab","volume":"32","author":"Liu","year":"2022","journal-title":"Struct. Eng. Int."},{"key":"10.1016\/j.aei.2026.104979_b0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.engfailanal.2022.106705","article-title":"Damage modes and residual deflections of multi-beam hollow slab bridge under car explosions","volume":"141","author":"Zhu","year":"2022","journal-title":"Eng. Fail. Anal."},{"key":"10.1016\/j.aei.2026.104979_b0045","doi-asserted-by":"crossref","DOI":"10.1016\/j.engfailanal.2021.105850","article-title":"Impact responses of precast hollow reinforced concrete beams with prestress tendons using high-fidelity physics-based simulations","volume":"131","author":"Do","year":"2022","journal-title":"Eng. Fail. Anal."},{"key":"10.1016\/j.aei.2026.104979_b0050","doi-asserted-by":"crossref","DOI":"10.1016\/j.compstruc.2023.107029","article-title":"Structural performance assessment of RC flexural members through crack-based fibre beam-column model updating","volume":"281","author":"Xiao","year":"2023","journal-title":"Comput. Struct."},{"key":"10.1016\/j.aei.2026.104979_b0055","article-title":"Comparative analysis of flexural performance of old full-scale hollow slab beams reinforced with fiber composites","volume":"338","author":"Su","year":"2022","journal-title":"Constr. Build. Mater."},{"key":"10.1016\/j.aei.2026.104979_b0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2023.105226","article-title":"Region of interest (ROI) extraction and crack detection for UAV-based bridge inspection using point cloud segmentation and 3D-to-2D projection","volume":"158","author":"Xiao","year":"2024","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2024.118302","article-title":"Corrosion-induced fragility of existing prestressed concrete girder bridges under traffic loads","volume":"314","author":"Nettis","year":"2024","journal-title":"Eng. Struct."},{"key":"10.1016\/j.aei.2026.104979_b0070","doi-asserted-by":"crossref","first-page":"6771","DOI":"10.1007\/s10518-025-02291-x","article-title":"Computer vision-based seismic assessment of RC simply supported bridges characterized by corroded circular piers","volume":"23","author":"Di Mucci","year":"2025","journal-title":"Bull. Earthq. Eng."},{"issue":"1","key":"10.1016\/j.aei.2026.104979_b0080","first-page":"90","article-title":"Effect of paving layer on transverse stiffness of hollow slab bridge after joint damage","volume":"40","author":"Xiao","year":"2024","journal-title":"Journal of Transport Science and Engineering"},{"key":"10.1016\/j.aei.2026.104979_b0085","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2023.117147","article-title":"Real-time damage identification of hinge joints in multi-girder bridges using recursive least squares solution of the characteristic equation","volume":"300","author":"Gong","year":"2024","journal-title":"Eng. Struct."},{"issue":"3","key":"10.1016\/j.aei.2026.104979_b0090","doi-asserted-by":"crossref","DOI":"10.1061\/(ASCE)BE.1943-5592.0001834","article-title":"Determining orders of modes sensitive to hinge joint damage in assembled hollow slab bridges","volume":"27","author":"Zhang","year":"2022","journal-title":"J. Bridg. Eng."},{"issue":"1","key":"10.1016\/j.aei.2026.104979_b0095","doi-asserted-by":"crossref","DOI":"10.1061\/(ASCE)CF.1943-5509.0001694","article-title":"Detecting hinge joint damage in hollow slab bridges using mode shapes extracted from vehicle response","volume":"36","author":"Zhang","year":"2022","journal-title":"J. Perform. Constr. Facil"},{"key":"10.1016\/j.aei.2026.104979_b0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.tws.2024.112429","article-title":"Theoretical study of extracting modal frequencies and hinge joint stiffness for thin-walled assembled multi-girder bridges from 3D vehicle","volume":"205","author":"Wang","year":"2024","journal-title":"Thin-Walled Struct."},{"key":"10.1016\/j.aei.2026.104979_b0105","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2025.120148","article-title":"Deep learning-based damage assessment of hinge joints for multi-girder bridges utilizing vehicle-induced bridge responses","volume":"333","author":"Wang","year":"2025","journal-title":"Eng. Struct."},{"key":"10.1016\/j.aei.2026.104979_b0110","doi-asserted-by":"crossref","DOI":"10.1155\/2023\/1834669","article-title":"Hinge joints performance assessment of a PC hollow slab bridge based on impact vibration testing","volume":"2023","author":"Xia","year":"2023","journal-title":"Struct. Control Health Monit."},{"key":"10.1016\/j.aei.2026.104979_b0115","doi-asserted-by":"crossref","DOI":"10.1016\/j.istruc.2023.105657","article-title":"A dynamic stiffness-based two-step method for damage identification of joints in hinged slab bridges using support vector machine","volume":"58","author":"Zhao","year":"2023","journal-title":"Structures"},{"key":"10.1016\/j.aei.2026.104979_b0120","doi-asserted-by":"crossref","DOI":"10.1016\/j.measurement.2024.116016","article-title":"A spectrum correlation matrix-based rapid damage identification method for joints in hinged slab bridges by sparse measurement","volume":"242","author":"Xu","year":"2025","journal-title":"Measurement"},{"key":"10.1016\/j.aei.2026.104979_b0125","doi-asserted-by":"crossref","first-page":"e3053","DOI":"10.1002\/stc.3053","article-title":"Joint deterioration detection based on field-identified lateral deflection influence lines for adjacent box girder bridges","volume":"29","author":"Yang","year":"2022","journal-title":"Struct. Control Health Monit."},{"key":"10.1016\/j.aei.2026.104979_b0140","doi-asserted-by":"crossref","first-page":"699","DOI":"10.3390\/buildings13030699","article-title":"Detection and damage evaluation of hinge joints in hollow slab bridges based on a light-load field test","volume":"13","author":"Guo","year":"2023","journal-title":"Buildings"},{"key":"10.1016\/j.aei.2026.104979_b0145","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2022.109631","article-title":"A hybrid method for damage detection and condition assessment of hinge joints in hollow slab bridges using physical models and vision-based measurements","volume":"183","author":"Hu","year":"2023","journal-title":"Mech. Syst. Sig. Process."},{"key":"10.1016\/j.aei.2026.104979_b0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2021.113648","article-title":"Bridge load testing and damage evaluation using model updating method","volume":"252","author":"Abedin","year":"2022","journal-title":"Eng. Struct."},{"key":"10.1016\/j.aei.2026.104979_b0155","doi-asserted-by":"crossref","DOI":"10.1016\/j.measurement.2023.113867","article-title":"Damage identification of hinge joint in hollow slab bridge based on model updating and orthogonal matching pursuit algorithm","volume":"224","author":"Li","year":"2024","journal-title":"Measurement"},{"key":"10.1016\/j.aei.2026.104979_b0160","doi-asserted-by":"crossref","first-page":"4851","DOI":"10.3390\/app13084851","article-title":"Transverse connectivity and durability evaluation of hollow slab bridges using surface damage and neural networks: Field test investigation","volume":"13","author":"Jiang","year":"2023","journal-title":"Appl. Sci."},{"key":"10.1016\/j.aei.2026.104979_b0165","doi-asserted-by":"crossref","first-page":"2920","DOI":"10.3390\/buildings14092920","article-title":"Bayesian inference and condition assessment based on the deflection of aging reinforced concrete hollow slab bridges","volume":"14","author":"Yan","year":"2024","journal-title":"Buildings"},{"key":"10.1016\/j.aei.2026.104979_b0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2020.111551","article-title":"A damage identification method for connections of adjacent box-beam bridges using vehicle-bridge interaction analysis and model updating","volume":"228","author":"Zhan","year":"2021","journal-title":"Eng. Struct."},{"key":"10.1016\/j.aei.2026.104979_b0175","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2025.112832","article-title":"An intelligent agent-based method for model updating of structures with multiple uncertain parameters via deep reinforcement learning","volume":"234","author":"Bruno","year":"2025","journal-title":"Mech. Syst. Sig. Process."},{"key":"10.1016\/j.aei.2026.104979_b0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2023.105146","article-title":"Concrete spalling damage detection and seismic performance evaluation for RC shear walls via 3D reconstruction technique and numerical model updating","volume":"156","author":"Gao","year":"2023","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0185","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2020.103389","article-title":"Metamodel-based pattern recognition approach for real-time identification of earthquake-induced damage in historic masonry structures","volume":"120","author":"Garc\u00eda-Mac\u00edas","year":"2020","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0190","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103818","article-title":"Structural evaluation of cracked shield tunnels using computer-vision-based model updating techniques","volume":"69","author":"Chang","year":"2026","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104979_b0195","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103714","article-title":"Vision-based geometric finite element model updating for cable suspension bridges","volume":"68","author":"Lee","year":"2025","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104979_b0200","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.autcon.2018.11.010","article-title":"Integration of reverse engineering and non-linear numerical analysis for the seismic assessment of historical adobe buildings","volume":"98","author":"Aguilar","year":"2019","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0205","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2025.112831","article-title":"Digital twin technique for automatic damage detection of historical buildings with an adaptive model updating approach","volume":"234","author":"Zhang","year":"2025","journal-title":"Mech. Syst. Sig. Process."},{"key":"10.1016\/j.aei.2026.104979_b0210","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.autcon.2019.04.021","article-title":"Non-destructive means and methods for structural diagnosis of masonry arch bridges","volume":"104","author":"S\u00e1nchez-Aparicio","year":"2019","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0215","first-page":"e2303","article-title":"Level 2 safety evaluation of concrete-filled steel tubular arch bridges incorporating structural health monitoring and inspection information based on China bridge standards","volume":"26","author":"Li","year":"2019","journal-title":"Struct. Control Health Monit."},{"key":"10.1016\/j.aei.2026.104979_b0220","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2022.104308","article-title":"Structural health control of historical steel structures using HBIM","volume":"140","author":"Bouzas","year":"2022","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0225","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.autcon.2018.03.014","article-title":"Method for developing and updating deterioration models for concrete bridge decks using GPR data","volume":"91","author":"Ghodoosi","year":"2018","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0230","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1111\/mice.12492","article-title":"An efficient algorithm for architecture design of Bayesian neural network in structural model updating","volume":"35","author":"Yin","year":"2020","journal-title":"Comput. Aided Civ. Inf. Eng."},{"key":"10.1016\/j.aei.2026.104979_b0235","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.autcon.2017.10.025","article-title":"Real-time structural health monitoring of a supertall building under construction based on visual modal identification strategy","volume":"85","author":"Park","year":"2018","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0240","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2020.103547","article-title":"Digital twin-based collapse fragility assessment of a long-span cable-stayed bridge under strong earthquakes","volume":"123","author":"Lin","year":"2021","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0255","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103721","article-title":"Predictive structural assessment with Bayesian deep learning","volume":"68","author":"Kuhn","year":"2025","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104979_b0260","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103185","article-title":"Quantitative multi-index residual capacities assessment of structural components through deep-learning-based image processing: A proof-of-concept study on masonry walls","volume":"65","author":"Cai","year":"2025","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104979_b0265","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2025.106641","article-title":"Explainable boosting machine for structural health assessment of reinforced concrete beams using crack width measurements","volume":"181","author":"Shamszadeh","year":"2026","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0270","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2025.106155","article-title":"Semi-supervised method for automated detection and quantitative assessment of corrosion states in structural members","volume":"174","author":"An","year":"2025","journal-title":"Autom. Constr."},{"key":"10.1016\/j.aei.2026.104979_b0275","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.113097","article-title":"Sustainable structural health assessment of heritage masonry towers using artificial intelligence and data-driven monitoring: Insights from the civic tower of Matelica","volume":"163","author":"Standoli","year":"2026","journal-title":"Eng. Appl. Artif. Intel."},{"key":"10.1016\/j.aei.2026.104979_b0280","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.106665","article-title":"Using Conceptual Graph modeling and inference to support the assessment and monitoring of bridge structural health","volume":"125","author":"Ndinga Okina","year":"2023","journal-title":"Eng. Appl. Artif. Intel."},{"key":"10.1016\/j.aei.2026.104979_b0285","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103956","article-title":"A piezoelectric sensing and machine learning integrated method for modulus inversion and structural strength prediction in asphalt pavements","volume":"69","author":"Ye","year":"2026","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104979_b0290","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.111282","article-title":"Application of latent variable models for hidden pattern identification and machine learning prediction improvement in structural engineering","volume":"156","author":"Shturmin","year":"2025","journal-title":"Eng. Appl. Artif. Intel."},{"key":"10.1016\/j.aei.2026.104979_b0295","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2025.110383","article-title":"Quantitative method for structural health evaluation under multiple performance metrics via multi-physics guided neural network","volume":"147","author":"Liu","year":"2025","journal-title":"Eng. Appl. Artif. Intel."},{"key":"10.1016\/j.aei.2026.104979_b0300","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2026.114002","article-title":"Model updating of structures by combining reduced order modelling and deep reinforcement learning","volume":"248","author":"Bruno","year":"2026","journal-title":"Mech. Syst. Sig. Process."},{"key":"10.1016\/j.aei.2026.104979_b0245","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102363","article-title":"Differentiable automatic structural optimization using graph deep learning","volume":"60","author":"Zhang","year":"2024","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104979_b0250","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2025.112618","article-title":"Towards efficient structural inverse analysis based on AI-driven differentiable optimization method","volume":"230","author":"Wang","year":"2025","journal-title":"Mech. Syst. Sig. Process."},{"key":"10.1016\/j.aei.2026.104979_b0130","doi-asserted-by":"crossref","DOI":"10.1016\/j.istruc.2024.105889","article-title":"A modified lateral load distribution model for hollow slab bridges considering the connecting effect of hinge joints","volume":"60","author":"Guo","year":"2024","journal-title":"Structures"},{"issue":"21","key":"10.1016\/j.aei.2026.104979_b0135","doi-asserted-by":"crossref","first-page":"11304","DOI":"10.3390\/app122111304","article-title":"Low-cost assessment method for existing adjacent beam bridges","volume":"12","author":"Wang","year":"2022","journal-title":"Appl. Sci."},{"key":"10.1016\/j.aei.2026.104979_b0305","article-title":"State-of-the-art AI-based computational analysis in civil engineering","volume":"33","author":"Wang","year":"2023","journal-title":"J. Ind. Inf. Integr."},{"key":"10.1016\/j.aei.2026.104979_b0310","doi-asserted-by":"crossref","first-page":"e1305","DOI":"10.1002\/widm.1305","article-title":"A review of automatic differentiation and its efficient implementation","volume":"9","author":"Margossian","year":"2019","journal-title":"WIREs Data Min. Knowl. Discovery"},{"issue":"4","key":"10.1016\/j.aei.2026.104979_b0315","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1198\/TECH.2009.08040","article-title":"Choosing the sample size of a computer experiment: A practical guide","volume":"51","author":"Loeppky","year":"2009","journal-title":"Technometrics"},{"issue":"32","key":"10.1016\/j.aei.2026.104979_b0320","doi-asserted-by":"crossref","first-page":"15849","DOI":"10.1073\/pnas.1903070116","article-title":"Reconciling modern machine-learning practice and the classical bias\u2013variance trade-off","volume":"116","author":"Belkin","year":"2019","journal-title":"Proc. Natl. Acad. Sci."},{"key":"10.1016\/j.aei.2026.104979_b0325","unstructured":"Kaplan J, McCandlish S, Henighan T, et al. Scaling laws for neural language models. arXiv preprint arXiv:2001.08361, 2020."},{"key":"10.1016\/j.aei.2026.104979_b0330","unstructured":"Rosenfeld JS, Rosenfeld A, Belinkov Y, et al. A constructive prediction of the generalization error across scales. International Conference on Learning Representations, 2020."},{"issue":"2","key":"10.1016\/j.aei.2026.104979_b0355","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1109\/TSE.2025.3525955","article-title":"Accuracy can lie: On the impact of surrogate model in configuration tuning","volume":"51","author":"Chen","year":"2025","journal-title":"IEEE Trans. Softw. Eng."},{"key":"10.1016\/j.aei.2026.104979_b0360","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2025.112395","article-title":"Bayesian generative kernel Gaussian process regression","volume":"227","author":"Kuok","year":"2025","journal-title":"Mech. Syst. Sig. Process."},{"key":"10.1016\/j.aei.2026.104979_b0365","doi-asserted-by":"crossref","first-page":"4083","DOI":"10.1007\/s12065-024-00973-0","article-title":"Optimizing performance of feedforward and convolutional neural networks through dynamic activation functions","volume":"17","author":"Rane","year":"2024","journal-title":"Evol. Intel."},{"issue":"12","key":"10.1016\/j.aei.2026.104979_b0335","doi-asserted-by":"crossref","DOI":"10.1061\/(ASCE)BE.1943-5592.0001495","article-title":"Recommendations for more accurate shear rating of prestressed concrete girder bridges","volume":"24","author":"Dymond","year":"2019","journal-title":"J. Bridg. Eng."},{"issue":"11","key":"10.1016\/j.aei.2026.104979_b0340","doi-asserted-by":"crossref","DOI":"10.1061\/(ASCE)BE.1943-5592.0001787","article-title":"Field load rating and grillage analysis method for skewed steel girder highway bridges","volume":"26","author":"Lu","year":"2021","journal-title":"J. Bridg. Eng."},{"key":"10.1016\/j.aei.2026.104979_b0345","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.advengsoft.2017.01.006","article-title":"Abaqus2Matlab: A suitable tool for finite element post-processing","volume":"105","author":"Papazafeiropoulos","year":"2017","journal-title":"Adv. Eng. Softw."},{"key":"10.1016\/j.aei.2026.104979_b0350","unstructured":"MathWorks, Inc., MATLAB R2024a, 2024."}],"container-title":["Advanced Engineering Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626006713?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626006713?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T00:32:38Z","timestamp":1781829158000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1474034626006713"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":72,"alternative-id":["S1474034626006713"],"URL":"https:\/\/doi.org\/10.1016\/j.aei.2026.104979","relation":{},"ISSN":["1474-0346"],"issn-type":[{"value":"1474-0346","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep learning surrogate-based differentiable optimisation inversion method for structural condition assessment of assembled slab girder bridges","name":"articletitle","label":"Article Title"},{"value":"Advanced Engineering Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.aei.2026.104979","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104979"}}