{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T13:41:37Z","timestamp":1782999697950,"version":"3.54.5"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100003399","name":"Shanghai Municipality Science and Technology Commission","doi-asserted-by":"publisher","award":["22YF1419100"],"award-info":[{"award-number":["22YF1419100"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFC3008302"],"award-info":[{"award-number":["2023YFC3008302"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFC3008300"],"award-info":[{"award-number":["2023YFC3008300"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004921","name":"Shanghai Jiao Tong University","doi-asserted-by":"publisher","award":["SL2022MS007"],"award-info":[{"award-number":["SL2022MS007"]}],"id":[{"id":"10.13039\/501100004921","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004921","name":"Shanghai Jiao Tong University","doi-asserted-by":"publisher","award":["GKZD010087"],"award-info":[{"award-number":["GKZD010087"]}],"id":[{"id":"10.13039\/501100004921","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72201171"],"award-info":[{"award-number":["72201171"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011251","name":"State Key Laboratory of Ocean Engineering","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011251","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100015796","name":"Shanghai Lingjun Program","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100015796","id-type":"DOI","asserted-by":"publisher"}]},{"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"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Reliability Engineering & System Safety"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1016\/j.ress.2025.111600","type":"journal-article","created":{"date-parts":[[2025,9,12]],"date-time":"2025-09-12T03:52:42Z","timestamp":1757649162000},"page":"111600","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":4,"special_numbering":"PA","title":["Towards effective decision support for structural design and risk management: An information-dependent probabilistic system representation enhanced with support vector machine and unfair sampling"],"prefix":"10.1016","volume":"266","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-1710-0249","authenticated-orcid":false,"given":"Wei-Heng","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-1443-2464","authenticated-orcid":false,"given":"Jianjun","family":"Qin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Da-Gang","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael Havbro","family":"Faber","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ress.2025.111600_b1","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.engstruct.2018.08.094","article-title":"Information-dependent seismic reliability assessment of bridge networks based on a correlation model","volume":"176","author":"Qin","year":"2018","journal-title":"Eng Struct"},{"key":"10.1016\/j.ress.2025.111600_b2","doi-asserted-by":"crossref","unstructured":"Liu M, Lu D-G, Qin J, Miao Y-Z, Zhang W-H, Zhu J-S, Faber MH. Risk-informed integrated design optimization for offshore wind farm electrical systems. Reliab Eng Syst Saf 250:110299. https:\/\/2.zoppoz.workers.dev:443\/http\/dx.doi.org\/10.1016\/j.ress.2024.110299.","DOI":"10.1016\/j.ress.2024.110299"},{"issue":"8","key":"10.1016\/j.ress.2025.111600_b3","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1111\/mice.12763","article-title":"Bayesian probabilistic representation of complex systems: With application to wave load modeling","volume":"37","author":"Glavind","year":"2022","journal-title":"Comput-Aided Civ Infrastruct Eng"},{"issue":"2","key":"10.1016\/j.ress.2025.111600_b4","article-title":"Hybrid Bayesian networks for reliability assessment of infrastructure systems","volume":"10","author":"Zwirglmaier","year":"2024","journal-title":"ASCE-ASME J Risk Uncertain Eng Syst, Part A: Civ Eng"},{"issue":"5","key":"10.1016\/j.ress.2025.111600_b5","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1111\/mice.13021","article-title":"A probabilistic deep reinforcement learning approach for optimal monitoring of a building adjacent to deep excavation","volume":"39","author":"Pan","year":"2024","journal-title":"Comput-Aided Civ Infrastruct Eng"},{"key":"10.1016\/j.ress.2025.111600_b6","series-title":"Probabilistic digital twin-informed risk-based inspection planning for offshore wind turbine structures","author":"Bull","year":"2023"},{"issue":"5","key":"10.1016\/j.ress.2025.111600_b7","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1080\/15732479.2010.539068","article-title":"Common cause effects in portfolio loss estimation","volume":"8","author":"Schubert","year":"2012","journal-title":"Struct Infrastruct Eng"},{"issue":"6","key":"10.1016\/j.ress.2025.111600_b8","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1111\/j.1467-8667.2012.00757.x","article-title":"Risk management of large RC structures within spatial information system","volume":"27","author":"Qin","year":"2012","journal-title":"Comput-Aided Civ Infrastruct Eng"},{"key":"10.1016\/j.ress.2025.111600_b9","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.strusafe.2018.09.002","article-title":"Optimal and acceptable reliabilities for structural design","volume":"76","author":"Fischer","year":"2019","journal-title":"Struct Saf"},{"key":"10.1016\/j.ress.2025.111600_b10","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.probengmech.2011.08.007","article-title":"A comparison of deterministic, reliability-based and risk-based structural optimization under uncertainty","volume":"28","author":"Beck","year":"2012","journal-title":"Probabilistic Eng Mech"},{"issue":"6","key":"10.1016\/j.ress.2025.111600_b11","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.strusafe.2009.06.007","article-title":"Structural optimization for performance-based design in earthquake engineering: Applications of neural networks","volume":"31","author":"M\u00f6ller","year":"2009","journal-title":"Struct Saf"},{"issue":"3","key":"10.1016\/j.ress.2025.111600_b12","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/0167-4730(93)90003-J","article-title":"A new look at the response surface approach for reliability analysis","volume":"12","author":"Rajashekhar","year":"1993","journal-title":"Struct Saf"},{"key":"10.1016\/j.ress.2025.111600_b13","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.strusafe.2018.06.003","article-title":"An active-learning algorithm that combines sparse polynomial chaos expansions and bootstrap for structural reliability analysis","volume":"75","author":"Marelli","year":"2018","journal-title":"Struct Saf"},{"key":"10.1016\/j.ress.2025.111600_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2024.110098","article-title":"An active learning Kriging model with approximating parallel strategy for structural reliability analysis","volume":"247","author":"Meng","year":"2024","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2025.111600_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2020.106684","article-title":"An active learning method combining deep neural network and weighted sampling for structural reliability analysis","volume":"140","author":"Xiang","year":"2020","journal-title":"Mech Syst Signal Process"},{"issue":"1","key":"10.1016\/j.ress.2025.111600_b16","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1007\/s00366-023-01790-2","article-title":"An importance sampling method for structural reliability analysis based on interpretable deep generative network","volume":"40","author":"Xiang","year":"2024","journal-title":"Eng Comput"},{"key":"10.1016\/j.ress.2025.111600_b17","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109126","article-title":"Support vector machine in structural reliability analysis: A review","author":"Roy","year":"2023","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2025.111600_b18","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.probengmech.2018.11.001","article-title":"Support vector regression based metamodeling for structural reliability analysis","volume":"55","author":"Roy","year":"2019","journal-title":"Probabilistic Eng Mech"},{"issue":"10","key":"10.1016\/j.ress.2025.111600_b19","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.1007\/s10483-006-1001-z","article-title":"Support vector machine for structural reliability analysis","volume":"27","author":"Li","year":"2006","journal-title":"Appl Math Mech"},{"key":"10.1016\/j.ress.2025.111600_b20","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.ress.2012.09.006","article-title":"Seismic reliability assessment of RC structures including soil\u2013structure interaction using wavelet weighted least squares support vector machine","volume":"110","author":"Khatibinia","year":"2013","journal-title":"Reliab Eng Syst Saf"},{"issue":"1","key":"10.1016\/j.ress.2025.111600_b21","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1109\/TSMCB.2008.2002909","article-title":"SVMs modeling for highly imbalanced classification","volume":"39","author":"Tang","year":"2008","journal-title":"IEEE Trans Syst Man Cybern B"},{"issue":"1","key":"10.1016\/j.ress.2025.111600_b22","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1080\/10286608.2019.1615476","article-title":"Faith and fakes\u2013dealing with critical information in decision analysis","volume":"36","author":"Nielsen","year":"2019","journal-title":"Civ Eng Environ Syst"},{"key":"10.1016\/j.ress.2025.111600_b23","series-title":"Safety and reliability of engineering systems and structures: proceedings of the 9th international conference on structural safety and reliability","first-page":"594","article-title":"On the application of Bayesian probabilistic networks for earthquake risk management","author":"Bayraktarli","year":"2005"},{"issue":"4","key":"10.1016\/j.ress.2025.111600_b24","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1115\/1.1491974","article-title":"Risk assessment of decommissioning options using Bayesian networks","volume":"124","author":"Faber","year":"2002","journal-title":"J Offshore Mech Arct Eng"},{"key":"10.1016\/j.ress.2025.111600_b25","doi-asserted-by":"crossref","DOI":"10.1016\/j.autcon.2023.105193","article-title":"Multi-status Bayesian network for analyzing collapse risk of excavation construction","volume":"158","author":"Lin","year":"2024","journal-title":"Autom Constr"},{"key":"10.1016\/j.ress.2025.111600_b26","article-title":"Bayesian network based decision support for predicting and mitigating delay risk in TBM tunnel projects","volume":"129","author":"Balta","year":"2021","journal-title":"Autom Constr"},{"key":"10.1016\/j.ress.2025.111600_b27","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.strusafe.2016.03.004","article-title":"Reliability analysis and updating of deteriorating systems with dynamic Bayesian networks","volume":"62","author":"Luque","year":"2016","journal-title":"Struct Saf"},{"key":"10.1016\/j.ress.2025.111600_b28","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2022.109916","article-title":"Quantifying the value of structural health monitoring information with measurement bias impacts in the framework of dynamic Bayesian Network","volume":"187","author":"Zhang","year":"2023","journal-title":"Mech Syst Signal Process"},{"issue":"3","key":"10.1016\/j.ress.2025.111600_b29","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/S0951-8320(02)00015-7","article-title":"Fast Monte Carlo reliability evaluation using support vector machine","volume":"76","author":"Rocco","year":"2002","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2025.111600_b30","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2020.107286","article-title":"Adaptive Bayesian support vector regression model for structural reliability analysis","volume":"206","author":"Cheng","year":"2021","journal-title":"Reliab Eng Syst Saf"},{"issue":"Supplement","key":"10.1016\/j.ress.2025.111600_b31","first-page":"92","article-title":"Analysis of global reliability and sensitivity of structures based on MLS-SVM","volume":"39","author":"Lu","year":"2022","journal-title":"Eng Mech"},{"key":"10.1016\/j.ress.2025.111600_b32","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.strusafe.2017.04.006","article-title":"An efficient reliability method combining adaptive support vector machine and Monte Carlo simulation","volume":"67","author":"Pan","year":"2017","journal-title":"Struct Saf"},{"key":"10.1016\/j.ress.2025.111600_b33","doi-asserted-by":"crossref","DOI":"10.1016\/j.strusafe.2020.101972","article-title":"Efficient methodology for seismic fragility curves estimation by active learning on Support Vector Machines","volume":"86","author":"Sainct","year":"2020","journal-title":"Struct Saf"},{"key":"10.1016\/j.ress.2025.111600_b34","unstructured":"Wu G, Chang EY. Class-boundary alignment for imbalanced dataset learning. In: ICML 2003 workshop on learning from imbalanced data sets II, Washington, DC. 2003, p. 49\u201356."},{"key":"10.1016\/j.ress.2025.111600_b35","doi-asserted-by":"crossref","DOI":"10.1016\/j.ress.2023.109578","article-title":"Two-stage support vector machine-enabled deep excavation settlement prediction considering class imbalance and multi-source uncertainties","volume":"241","author":"Pan","year":"2024","journal-title":"Reliab Eng Syst Saf"},{"key":"10.1016\/j.ress.2025.111600_b36","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.probengmech.2015.06.006","article-title":"MCMC algorithms for subset simulation","volume":"41","author":"Papaioannou","year":"2015","journal-title":"Probabilistic Eng Mech"},{"key":"10.1016\/j.ress.2025.111600_b37","series-title":"Structural global reliability methods and nonlinear global seismic reliability analysis of RC frames","author":"Song","year":"2012"},{"key":"10.1016\/j.ress.2025.111600_b38","series-title":"Code for seismic design of buildings","year":"2010"},{"issue":"1","key":"10.1016\/j.ress.2025.111600_b39","first-page":"137","article-title":"OpenSees command language manual","volume":"264","author":"Mazzoni","year":"2006","journal-title":"Pac Earthq Eng Res (PEER) Cent"},{"issue":"11","key":"10.1016\/j.ress.2025.111600_b40","doi-asserted-by":"crossref","first-page":"1330","DOI":"10.1061\/(ASCE)ST.1943-541X.0000231","article-title":"Probabilistic push-over analysis of structural and soil-structure systems","volume":"136","author":"Barbato","year":"2010","journal-title":"J Struct Eng"}],"container-title":["Reliability Engineering & System Safety"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0951832025008002?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0951832025008002?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T01:08:48Z","timestamp":1773104928000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/linkinghub.elsevier.com\/retrieve\/pii\/S0951832025008002"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":40,"alternative-id":["S0951832025008002"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.ress.2025.111600","relation":{},"ISSN":["0951-8320"],"issn-type":[{"value":"0951-8320","type":"print"}],"subject":[],"published":{"date-parts":[[2026,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Towards effective decision support for structural design and risk management: An information-dependent probabilistic system representation enhanced with support vector machine and unfair sampling","name":"articletitle","label":"Article Title"},{"value":"Reliability Engineering & System Safety","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.ress.2025.111600","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"111600"}}