{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T21:47:58Z","timestamp":1776289678912,"version":"3.50.1"},"reference-count":52,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52179128"],"award-info":[{"award-number":["52179128"]}],"id":[{"id":"10.13039\/501100001809","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":[[2026,9]]},"DOI":"10.1016\/j.aei.2026.104688","type":"journal-article","created":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T16:44:01Z","timestamp":1776271441000},"page":"104688","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["Probabilistic dynamic model for high concrete-faced rockfill dam settlement prediction and anomaly identification"],"prefix":"10.1016","volume":"74","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7698-920X","authenticated-orcid":false,"given":"Jianye","family":"Ma","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3753-4455","authenticated-orcid":false,"given":"Dongjian","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.aei.2026.104688_b0005","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1061\/(ASCE)GM.1943-5622.0001232","article-title":"spatial estimation of material parameters and refined finite-element analysis of rockfill dam based on construction digitization","volume":"18","author":"Chen","year":"2018","journal-title":"Int. J. Geomech."},{"key":"10.1016\/j.aei.2026.104688_b0010","doi-asserted-by":"crossref","first-page":"4376","DOI":"10.1007\/s12205-024-1964-9","article-title":"Spatial estimation method of improved long-term deformation model parameters for concrete faced rockfill dam","volume":"28","author":"Chen","year":"2024","journal-title":"KSCE J. Civ. Eng."},{"key":"10.1016\/j.aei.2026.104688_b0015","doi-asserted-by":"crossref","first-page":"3467","DOI":"10.1007\/s11440-023-02098-7","article-title":"Development and evaluation of a practical nonlinear elastic constitutive model for rockfill dam deformation simulation based on monitoring results","volume":"19","author":"Wang","year":"2024","journal-title":"Acta Geotech."},{"key":"10.1016\/j.aei.2026.104688_b0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2025.103559","article-title":"Structural damage identification method of concrete dam based on multi-fidelity surrogate model collaboratively corrected by monitoring and simulation information","volume":"67","author":"Guo","year":"2025","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104688_b0025","article-title":"Hydro-steel structure digital twins: application in structural health monitoring and maintenance of large-scale reservoir","volume":"62","author":"Li","year":"2024","journal-title":"Adv. Eng. Inf."},{"key":"10.1016\/j.aei.2026.104688_b0030","first-page":"103","article-title":"A critical review of machine learning application models in dam settlement monitoring","volume":"9","author":"Beiranvand","year":"2025","journal-title":"J. Soft Comput. Civil Eng."},{"key":"10.1016\/j.aei.2026.104688_b0035","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1007\/s12517-022-11005-5","article-title":"Performance efficiency of data-based hybrid intelligent approaches to predict crest settlement in rockfill dams","volume":"15","author":"Seifollahi","year":"2022","journal-title":"Arab. J. Geosci."},{"key":"10.1016\/j.aei.2026.104688_b0040","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1061\/(ASCE)GM.1943-5622.0001912","article-title":"Multiple nonlinear regression models for predicting deformation behavior of concrete-face rockfill dams","volume":"21","author":"Wen","year":"2021","journal-title":"Int. J. Geomech."},{"key":"10.1016\/j.aei.2026.104688_b0045","doi-asserted-by":"crossref","first-page":"7973","DOI":"10.1007\/s10064-021-02403-2","article-title":"A novel settlement forecasting model for rockfill dams based on physical causes","volume":"80","author":"Chen","year":"2021","journal-title":"Bull. Eng. Geol. Environ."},{"key":"10.1016\/j.aei.2026.104688_b0050","doi-asserted-by":"crossref","first-page":"5801","DOI":"10.1007\/s13369-020-05285-w","article-title":"A prediction model for deformation behavior of concrete face rockfill dams based on the threshold regression method","volume":"46","author":"Li","year":"2021","journal-title":"Arab. J. Sci. Eng."},{"key":"10.1016\/j.aei.2026.104688_b0055","first-page":"746","article-title":"A novel component separation method for deformation monitoring of rockfill dams","volume":"12","author":"Li","year":"2024","journal-title":"Struct. Health Monit."},{"key":"10.1016\/j.aei.2026.104688_b0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.compgeo.2023.105611","article-title":"Predicting the deformation behaviour of concrete face rockfill dams by combining support vector machine and AdaBoost ensemble algorithm","volume":"161","author":"Wen","year":"2023","journal-title":"Comput. Geotech."},{"key":"10.1016\/j.aei.2026.104688_b0065","doi-asserted-by":"crossref","first-page":"2999","DOI":"10.1038\/s41598-024-60944-4","article-title":"Presenting the AI models in predicting the settlement of earth dams using the results of spatiotemporal clustering and k-means algorithm","volume":"14","author":"Beiranvand","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.aei.2026.104688_b0070","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1061\/(ASCE)CF.1943-5509.0001485","article-title":"Statistically optimized back-propagation neural-network model and its application for deformation monitoring and prediction of concrete-face rockfill dams","volume":"34","author":"Han","year":"2020","journal-title":"J. Perform. Constr. Facil"},{"key":"10.1016\/j.aei.2026.104688_b0075","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1007\/s13349-023-00691-8","article-title":"Multi-sensor data fusion with AI-RBFN in settlement surveillance of embankment dams: application to a rockfill dam in Algeria","volume":"13","author":"Belhadj","year":"2023","journal-title":"J. Civil Struct. Health Monit."},{"key":"10.1016\/j.aei.2026.104688_b0080","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1007\/s13349-022-00641-w","article-title":"Prediction of long-term maximum settlement deformation of concrete face rockfill dams using hybrid support vector regression optimized with HHO algorithm","volume":"13","author":"Li","year":"2023","journal-title":"J. Civil Struct. Health Monit."},{"key":"10.1016\/j.aei.2026.104688_b0085","doi-asserted-by":"crossref","first-page":"2157","DOI":"10.3390\/w14142157","article-title":"Prediction for the settlement of concrete face rockfill dams using optimized LSTM model via correlated monitoring data","volume":"14","author":"Hu","year":"2022","journal-title":"Water"},{"key":"10.1016\/j.aei.2026.104688_b0090","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.wse.2023.09.005","article-title":"Deformation prediction model of concrete face rockfill dams based on an improved random forest model","volume":"16","author":"Li","year":"2023","journal-title":"Water Sci. Eng."},{"key":"10.1016\/j.aei.2026.104688_b0095","doi-asserted-by":"crossref","unstructured":"X. Zhou, Y. Zhang, G. Ma, Deformation analysis of the 233 m Shuibuya rockfill dam using breakage mechanics (2019) 267\u2013276. https:\/\/doi.org\/10.1061\/9780784482070.026.","DOI":"10.1061\/9780784482070.026"},{"key":"10.1016\/j.aei.2026.104688_b0100","series-title":"Deformation Analysis of the 233 m Shuibuya Rockfill Dam Using Breakage Mechanics","year":"2019"},{"key":"10.1016\/j.aei.2026.104688_b0105","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1139\/cgj-2016-0193","article-title":"An empirical method for predicting post-construction settlement of concrete face rockfill dams","volume":"54","author":"Kermani","year":"2017","journal-title":"Can. Geotech. J."},{"key":"10.1016\/j.aei.2026.104688_b0110","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1680\/jgeot.17.P.095","article-title":"A statistical review of the behaviour of concrete-face rockfill dams based on case histories","volume":"68","author":"Wen","year":"2018","journal-title":"G\u00e9otechnique"},{"key":"10.1016\/j.aei.2026.104688_b0115","first-page":"103","article-title":"A critical review of machine learning application models in dam settlement monitoring","volume":"9","author":"Document","year":"2025","journal-title":"J. Soft Comp. Civil Eng."},{"key":"10.1016\/j.aei.2026.104688_b0120","doi-asserted-by":"crossref","DOI":"10.1016\/j.engstruct.2024.117899","article-title":"Physical data-driven modeling of deformation mechanism constraints on earth-rock dams based on deep feature knowledge distillation and finite element method","volume":"307","author":"Tian","year":"2024","journal-title":"Eng. Struct."},{"key":"10.1016\/j.aei.2026.104688_b0125","series-title":"Safety Monitoring Theory and Appli-cation of Hydraulic Structures","author":"Wu","year":"2003"},{"key":"10.1016\/j.aei.2026.104688_b0130","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1680\/geot.2007.57.3.289","article-title":"Theoretical investigation of the time-dependent behaviour of rockfill","volume":"57","author":"Oldecop","year":"2007","journal-title":"G\u00e9otechnique"},{"key":"10.1016\/j.aei.2026.104688_b0135","series-title":"Concrete Face Rockfill Dams","author":"Fu","year":"1993"},{"key":"10.1016\/j.aei.2026.104688_b0140","series-title":"Experience and Innovation in Earth Rock Dam Engineering","author":"Gu","year":"2004"},{"key":"10.1016\/j.aei.2026.104688_b0145","unstructured":"Bhargob Deka, Van-Dai Vuong, James-A. Goulet (Eds.), Dam behaviour prediction using an ensemble of Bayesian dynamic linear model and Bayesian LSTM networks, 2022."},{"key":"10.1016\/j.aei.2026.104688_b0150","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/14498596.2017.1330711","article-title":"Dynamic modelling of displacements on an embankment dam using the Kalman filter","volume":"63","author":"Gamse","year":"2018","journal-title":"J. Spat. Sci."},{"key":"10.1016\/j.aei.2026.104688_b0155","doi-asserted-by":"crossref","DOI":"10.1016\/j.measurement.2024.115094","article-title":"Prediction intervals for concrete face sandy gravel dam settlement using Kalman filter-based kernel extreme learning machine","volume":"236","author":"Zhou","year":"2024","journal-title":"Measurement"},{"key":"10.1016\/j.aei.2026.104688_b0160","article-title":"Long-term deformation safety evaluation method of concrete dams based on the time-varying stability of concrete material","volume":"36","author":"Song","year":"2023","journal-title":"Mater. Today Commun."},{"key":"10.1016\/j.aei.2026.104688_b0165","doi-asserted-by":"crossref","first-page":"2929","DOI":"10.1109\/TAC.2013.2258782","article-title":"A new extension of newton algorithm for nonlinear system modelling using RBF neural networks","volume":"58","author":"Zhang","year":"2013","journal-title":"IEEE Trans. Automat. Contr."},{"key":"10.1016\/j.aei.2026.104688_b0170","doi-asserted-by":"crossref","first-page":"476","DOI":"10.1049\/ip-cta:20000549","article-title":"Analysis of minimal radial basis function network algorithm for real-time identification of nonlinear dynamic systems","volume":"147","author":"Li","year":"2000","journal-title":"IEE Proc Control Theory Appl."},{"key":"10.1016\/j.aei.2026.104688_b0175","doi-asserted-by":"crossref","unstructured":"J.J. Dabrowski, Y. Zhang, A. Rahman, ForecastNet: A time-variant deep feed-forward neural network architecture for multi-step-ahead time-series forecasting, in: Neural Information Processing, Cham, Springer International Publishing, Cham, 2020, pp.579\u2013591.","DOI":"10.1007\/978-3-030-63836-8_48"},{"key":"10.1016\/j.aei.2026.104688_b0180","doi-asserted-by":"crossref","first-page":"1161","DOI":"10.1109\/TAC.1982.1103112","article-title":"Bounded error adaptive control","volume":"27","author":"Peterson","year":"1982","journal-title":"IEEE Trans. Automat. Contr."},{"key":"10.1016\/j.aei.2026.104688_b0185","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1177\/1475921719864265","article-title":"An online anomaly recognition and early warning model for dam safety monitoring data","volume":"19","author":"Li","year":"2020","journal-title":"Struct. Health Monit."},{"key":"10.1016\/j.aei.2026.104688_b0190","doi-asserted-by":"crossref","first-page":"1183","DOI":"10.1177\/14759217211025766","article-title":"A three-stage online anomaly identification model for monitoring data in dams","volume":"21","author":"Xu","year":"2022","journal-title":"Struct. Health Monit."},{"key":"10.1016\/j.aei.2026.104688_b0195","first-page":"47","article-title":"A data-driven real-time evaluation method for safety risk of the anti-seepage system in high-core rockfill dams","volume":"16","author":"Guo","year":"2025","journal-title":"Struct. Health Monit."},{"key":"10.1016\/j.aei.2026.104688_b0200","unstructured":"Y. Gal, R. McAllister, C.E. Rasmussen, Improving PILCO with Bayesian neural network dynamics models, in: Data-efficient machine learning workshop, ICML, 2016, p.25."},{"key":"10.1016\/j.aei.2026.104688_b0205","doi-asserted-by":"crossref","first-page":"65","DOI":"10.3390\/infrastructures4040065","article-title":"From theory to field evidence: observations on the evolution of the settlements of an earthfill dam, over long time scales","volume":"4","author":"Pytharouli","year":"2019","journal-title":"Infrastructures"},{"key":"10.1016\/j.aei.2026.104688_b0210","first-page":"1","article-title":"Construction and analysis of slope plane deformation of high CFRD based on statistical analysis of multi\u2010points monitoring data","volume":"7","author":"Zhou","year":"2025","journal-title":"Eng. Rep."},{"key":"10.1016\/j.aei.2026.104688_b0215","doi-asserted-by":"crossref","DOI":"10.1016\/j.compgeo.2024.106518","article-title":"ResGRU: a deep learning approach for settlement prediction in CFRD based on the spatiotemporal feature fusion method","volume":"173","author":"Zhang","year":"2024","journal-title":"Comput. Geotech."},{"key":"10.1016\/j.aei.2026.104688_b0220","series-title":"In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"1930","article-title":"Modeling task relationships in multi-task learning with multi-gate mixture-of-experts","author":"Ma","year":"2018"},{"key":"10.1016\/j.aei.2026.104688_b0225","unstructured":"S. Bai, J.Z. Kolter, V. Koltun, An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling (2018). https:\/\/doi.org\/10.48550\/arXiv.1803.01271."},{"key":"10.1016\/j.aei.2026.104688_b0230","doi-asserted-by":"crossref","first-page":"1232","DOI":"10.1016\/j.ress.2010.07.014","article-title":"Model validation under epistemic uncertainty","volume":"96","author":"Sankararaman","year":"2011","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"10.1016\/j.aei.2026.104688_b0235","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s10994-021-05946-3","article-title":"Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods","volume":"110","author":"H\u00fcllermeier","year":"2021","journal-title":"Mach. Learn."},{"key":"10.1016\/j.aei.2026.104688_b0240","unstructured":"Y. Gal, Z. Ghahramani, Dropout as a Bayesian approximation: representing model uncertainty in deep learning (2016). https:\/\/doi.org\/10.48550\/arXiv.1506.02142."},{"key":"10.1016\/j.aei.2026.104688_b0245","series-title":"Analyze on Development Prospects of 300m Level Ultra-High CFRD from Shuibuya High CFRD","year":"2010"},{"key":"10.1016\/j.aei.2026.104688_b0250","doi-asserted-by":"crossref","first-page":"822","DOI":"10.1061\/(ASCE)0733-9410(1990)116:5(822)","article-title":"Nonlinear analysis of concrete face rockfill dam","volume":"116","author":"Khalid","year":"1990","journal-title":"J. Geotech. Engrg."},{"key":"10.1016\/j.aei.2026.104688_b0255","first-page":"1","article-title":"Back analysis of creep deformation of rockfill dams","author":"Shen","year":"1998","journal-title":"J. Hydraul. Eng."},{"key":"10.1016\/j.aei.2026.104688_b0260","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1061\/JSFEAQ.0001133","article-title":"A model for the mechanics of jointed rock","volume":"94","author":"Goodman","year":"1968","journal-title":"J. Soil Mech. and Found. Div."}],"container-title":["Advanced Engineering Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626003800?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1474034626003800?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T20:59:47Z","timestamp":1776286787000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1474034626003800"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":52,"alternative-id":["S1474034626003800"],"URL":"https:\/\/doi.org\/10.1016\/j.aei.2026.104688","relation":{},"ISSN":["1474-0346"],"issn-type":[{"value":"1474-0346","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Probabilistic dynamic model for high concrete-faced rockfill dam settlement prediction and anomaly identification","name":"articletitle","label":"Article Title"},{"value":"Advanced Engineering Informatics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.aei.2026.104688","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":"104688"}}