{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T07:48:39Z","timestamp":1777880919694,"version":"3.51.4"},"reference-count":53,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100012542","name":"Sichuan Province Science and Technology Support Program","doi-asserted-by":"publisher","award":["2024NSFSC2029"],"award-info":[{"award-number":["2024NSFSC2029"]}],"id":[{"id":"10.13039\/100012542","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.engappai.2026.114063","type":"journal-article","created":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T22:49:07Z","timestamp":1770850147000},"page":"114063","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Adaptive critical speed prediction for straddle-type monorail operational safety: A meta-learning framework with few-shot deployment"],"prefix":"10.1016","volume":"169","author":[{"given":"Junchao","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0784-701X","authenticated-orcid":false,"given":"Ao","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shangwu","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianjie","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiping","family":"Du","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2026.114063_bib1","doi-asserted-by":"crossref","first-page":"3253","DOI":"10.1007\/s11071-020-05468-y","article-title":"Human action recognition using lie group features and convolutional neural networks","volume":"99","author":"Cai","year":"2020","journal-title":"Nonlinear Dyn."},{"key":"10.1016\/j.engappai.2026.114063_bib2","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.109980","article-title":"Few-shot remaining useful life prediction based on Bayesian meta-learning with predictive uncertainty calibration","volume":"142","author":"Chang","year":"2025","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2026.114063_bib3","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2021.108398","article-title":"Design of a precise linear-rotary positioning stage for optical focusing based on the stick-slip mechanism","volume":"165","author":"Chang","year":"2022","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114063_bib4","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1007\/s44196-024-00639-w","article-title":"Prediction of remaining useful life of aero-engines based on CNN-LSTM-Attention","volume":"17","author":"Deng","year":"2024","journal-title":"Int. J. Comput. Intell. Syst."},{"key":"10.1016\/j.engappai.2026.114063_bib5","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1080\/13873950701742754","article-title":"New features of the software MatCont for bifurcation analysis of dynamical systems","volume":"14","author":"Dhooge","year":"2008","journal-title":"Math. Comput. Model. Dyn. Syst."},{"key":"10.1016\/j.engappai.2026.114063_bib6","doi-asserted-by":"crossref","first-page":"5514","DOI":"10.1109\/TNNLS.2021.3070878","article-title":"A high-efficient hybrid physics-informed neural networks based on convolutional neural network","volume":"33","author":"Fang","year":"2021","journal-title":"IEEE Transact. Neural Networks Learn. Syst."},{"key":"10.1016\/j.engappai.2026.114063_bib7","series-title":"International Conference on Machine Learning","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","author":"Finn","year":"2017"},{"key":"10.1016\/j.engappai.2026.114063_bib8","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2020.107189","article-title":"Temperature-dependent noise tendency prediction of the disc braking system","volume":"149","author":"Gao","year":"2021","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114063_bib9","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1038\/s42256-020-00242-6","article-title":"Moving beyond generalization to accurate interpretation of flexible models","volume":"2","author":"Genkin","year":"2020","journal-title":"Nat. Mach. Intell."},{"key":"10.1016\/j.engappai.2026.114063_bib10","first-page":"4540","article-title":"Reviews on current situation and development of straddle-type monorail tour transit system in China","volume":"52","author":"Guo","year":"2021","journal-title":"J. Cent. S. Univ."},{"key":"10.1016\/j.engappai.2026.114063_bib11","article-title":"The limit of the lateral fundamental frequency and comfort analysis of a straddle-type monorail tour transit system","volume":"12","author":"Guo","year":"2022","journal-title":"Appl. Sci."},{"key":"10.1016\/j.engappai.2026.114063_bib12","doi-asserted-by":"crossref","first-page":"989","DOI":"10.1007\/s11071-021-06373-8","article-title":"Bifurcation analysis of a railway wheelset with nonlinear wheel\u2013rail contact","volume":"104","author":"Guo","year":"2021","journal-title":"Nonlinear Dyn."},{"key":"10.1016\/j.engappai.2026.114063_bib13","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1080\/00423114.2022.2050770","article-title":"Double-parameter hopf bifurcation analysis of a high-speed rail vehicle with an alternative wheel\/rail contact approximation","volume":"61","author":"Guo","year":"2023","journal-title":"Veh. Syst. Dyn."},{"key":"10.1016\/j.engappai.2026.114063_bib14","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"10.1016\/j.engappai.2026.114063_bib15","doi-asserted-by":"crossref","first-page":"1418","DOI":"10.1080\/00423114.2020.1755046","article-title":"Passive radial mechanism of a bogie with the auxiliary steering device for the straddle monorail vehicle","volume":"59","author":"Ji","year":"2021","journal-title":"Veh. Syst. Dyn."},{"key":"10.1016\/j.engappai.2026.114063_bib16","doi-asserted-by":"crossref","first-page":"77","DOI":"10.3390\/rs17010077","article-title":"Metatrans-fstsf: a transformer-based meta-learning framework for few-shot time series forecasting in flood prediction","volume":"17","author":"Jiang","year":"2024","journal-title":"Remote Sens."},{"key":"10.1016\/j.engappai.2026.114063_bib17","first-page":"1","article-title":"Impact vibration behavior of railway vehicles: a state-of-the-art overview","author":"Jing","year":"2021","journal-title":"Acta Mech. Sin."},{"key":"10.1016\/j.engappai.2026.114063_bib18","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1016\/j.jsv.2005.12.028","article-title":"Dynamic response of a monorail steel bridge under a moving train","volume":"294","author":"Lee","year":"2006","journal-title":"J. Sound Vib."},{"key":"10.1016\/j.engappai.2026.114063_bib19","doi-asserted-by":"crossref","first-page":"1999","DOI":"10.1016\/j.engstruct.2005.06.014","article-title":"Dynamic response analysis of monorail bridges under moving trains and riding comfort of trains","volume":"27","author":"Lee","year":"2005","journal-title":"Eng. Struct."},{"key":"10.1016\/j.engappai.2026.114063_bib20","doi-asserted-by":"crossref","first-page":"1407","DOI":"10.1080\/00423114.2019.1632464","article-title":"Radial adjustment mechanism of a newly designed coupled-bogie for the straddle-type monorail vehicle","volume":"58","author":"Leng","year":"2020","journal-title":"Veh. Syst. Dyn."},{"key":"10.1016\/j.engappai.2026.114063_bib21","doi-asserted-by":"crossref","DOI":"10.1016\/j.cnsns.2020.105472","article-title":"Long-term dynamical behavior of the wave model with locally distributed frictional and viscoelastic damping","volume":"92","author":"Li","year":"2021","journal-title":"Commun. Nonlinear Sci. Numer. Simul."},{"key":"10.1016\/j.engappai.2026.114063_bib22","doi-asserted-by":"crossref","first-page":"3728","DOI":"10.3390\/app15073728","article-title":"Suppression of multiple reflection interference signals in GPR images caused by rebar using VAE-GAN","volume":"15","author":"Li","year":"2025","journal-title":"Appl. Sci."},{"key":"10.1016\/j.engappai.2026.114063_bib23","doi-asserted-by":"crossref","first-page":"8003","DOI":"10.1109\/TII.2021.3058426","article-title":"Model-agnostic meta-learning with optimal alternative scaling value and its application to industrial soft sensing","volume":"17","author":"Lu","year":"2021","journal-title":"IEEE Trans. Ind. Inf."},{"key":"10.1016\/j.engappai.2026.114063_bib24","doi-asserted-by":"crossref","first-page":"185099","DOI":"10.1109\/ACCESS.2019.2960537","article-title":"Deep learning for track quality evaluation of high-speed railway based on vehicle-body vibration prediction","volume":"7","author":"Ma","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.114063_bib25","doi-asserted-by":"crossref","first-page":"2093","DOI":"10.1007\/s11071-022-07926-1","article-title":"Double grazing bifurcations of the non-smooth railway wheelset systems","volume":"111","author":"Miao","year":"2023","journal-title":"Nonlinear Dyn."},{"key":"10.1016\/j.engappai.2026.114063_bib26","doi-asserted-by":"crossref","DOI":"10.1016\/j.aei.2024.102870","article-title":"A task-oriented theil index-based meta-learning network with gradient calibration strategy for rotating machinery fault diagnosis with limited samples","volume":"62","author":"Mu","year":"2024","journal-title":"Adv. Eng. Inform."},{"key":"10.1016\/j.engappai.2026.114063_bib27","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1016\/j.jcp.2018.10.045","article-title":"Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations","volume":"378","author":"Raissi","year":"2019","journal-title":"J. Comput. Phys."},{"key":"10.1016\/j.engappai.2026.114063_bib28","doi-asserted-by":"crossref","first-page":"2746","DOI":"10.1109\/TCYB.2023.3338768","article-title":"Meta-learning with distributional similarity preference for few-shot fault diagnosis under varying working conditions","volume":"54","author":"Ren","year":"2023","journal-title":"IEEE Trans. Cybern."},{"key":"10.1016\/j.engappai.2026.114063_bib29","series-title":"International Conference on Machine Learning","first-page":"1842","article-title":"Meta-learning with memory-augmented neural networks","author":"Santoro","year":"2016"},{"key":"10.1016\/j.engappai.2026.114063_bib30","doi-asserted-by":"crossref","DOI":"10.1177\/16878132221143573","article-title":"Abnormal vibration analysis of metro axlebox based on vehicle-track coupling system","volume":"15","author":"Shi","year":"2023","journal-title":"Adv. Mech. Eng."},{"key":"10.1016\/j.engappai.2026.114063_bib31","article-title":"Prototypical networks for few-shot learning","volume":"30","author":"Snell","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.engappai.2026.114063_bib32","doi-asserted-by":"crossref","DOI":"10.1016\/j.jsv.2025.119158","article-title":"Shimmy mechanics and nonlinear vibration characteristics of monorail vehicle","author":"Tian","year":"2025","journal-title":"J. Sound Vib."},{"key":"10.1016\/j.engappai.2026.114063_bib33","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.neucom.2022.04.078","article-title":"Meta-learning approaches for learning-to-learn in deep learning: a survey","volume":"494","author":"Tian","year":"2022","journal-title":"Neurocomputing"},{"key":"10.1016\/j.engappai.2026.114063_bib34","doi-asserted-by":"crossref","first-page":"4087","DOI":"10.1007\/s11071-022-08056-4","article-title":"Parametric and self-excited oscillation produced in railway wheelset due to mass imbalance and large wheel tread angle","volume":"111","author":"Umemoto","year":"2023","journal-title":"Nonlinear Dyn."},{"key":"10.1016\/j.engappai.2026.114063_bib35","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.jmsy.2021.12.009","article-title":"Meta domain generalization for smart manufacturing: tool wear prediction with small data","volume":"62","author":"Wang","year":"2022","journal-title":"J. Manuf. Syst."},{"key":"10.1016\/j.engappai.2026.114063_bib36","series-title":"IOP Conference Series: Materials Science and Engineering","article-title":"Study on vibration acceleration prediction model of track inspection vehicle based on BP neural network","author":"Wang","year":"2018"},{"key":"10.1016\/j.engappai.2026.114063_bib37","article-title":"An adaptive fused domain-cycling variational generative adversarial network for machine fault diagnosis under data scarcity","author":"Wang","year":"2025","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.engappai.2026.114063_bib38","first-page":"150","article-title":"Research on a prediction method of train body vibrations based on rail inspection data","volume":"41","author":"Wang","year":"2021","journal-title":"Noise Vibr. Contr."},{"key":"10.1016\/j.engappai.2026.114063_bib39","article-title":"Running stability for monorail vehicles based on the magic-formula tire model","author":"Wen","year":"2024","journal-title":"Int. J. Struct. Stabil. Dynam."},{"key":"10.1016\/j.engappai.2026.114063_bib40","first-page":"459","article-title":"Study on the tire uneven wear mechanism of the running wheel of monorail vehicles","volume":"19","author":"Wen","year":"2016","journal-title":"J. Appl. Sci. Eng."},{"key":"10.1016\/j.engappai.2026.114063_bib41","first-page":"588","article-title":"Research on parameter optimization based on multi-body dynamics model of monorail vehicle aiming at reducing running wheel wear","volume":"236","author":"Wen","year":"2022","journal-title":"Proc. Inst. Mech. Eng. - Part K J. Multi-body Dyn."},{"key":"10.1016\/j.engappai.2026.114063_bib42","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1007\/s40864-017-0065-1","article-title":"Research on vertical coupling dynamics of monorail vehicle at finger-band","volume":"3","author":"Xu","year":"2017","journal-title":"Urban Rail Transit."},{"key":"10.1016\/j.engappai.2026.114063_bib43","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1177\/0957456520947998","article-title":"Research on dynamic behavior of train dynamic model of straddle-type monorail","volume":"51","author":"Yang","year":"2020","journal-title":"Noise Vib. Worldw."},{"key":"10.1016\/j.engappai.2026.114063_bib44","doi-asserted-by":"crossref","first-page":"149","DOI":"10.3901\/JME.2022.03.149","article-title":"Gear degradation trend prediction by meta-learning gated recurrent unit networks under few samples","volume":"58","author":"Yu","year":"2022","journal-title":"J. Mech. Eng."},{"key":"10.1016\/j.engappai.2026.114063_bib45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s40747-024-01660-4","article-title":"A robust adaptive meta-sample generation method for few-shot time series prediction","volume":"11","author":"Zhang","year":"2025","journal-title":"Complex Intell. Syst."},{"key":"10.1016\/j.engappai.2026.114063_bib46","doi-asserted-by":"crossref","first-page":"2155","DOI":"10.1007\/s11071-024-10356-w","article-title":"Influence of steady aerodynamic loads on hunting stability of high-speed trains","volume":"113","author":"Zhang","year":"2025","journal-title":"Nonlinear Dyn."},{"key":"10.1016\/j.engappai.2026.114063_bib47","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1080\/00423114.2023.2252536","article-title":"Bifurcation analysis of the bogie system with time delay and the influence of parameters on the system","volume":"62","author":"Zhang","year":"2024","journal-title":"Veh. Syst. Dyn."},{"key":"10.1016\/j.engappai.2026.114063_bib48","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2025.122166","article-title":"Image deblurring method based on GAN with a channel attention mechanism","volume":"713","author":"Zhang","year":"2025","journal-title":"Inf. Sci."},{"key":"10.1016\/j.engappai.2026.114063_bib49","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.jmsy.2024.07.002","article-title":"A meta-PINN framework for online operational monitoring of high-power induction furnace","volume":"76","author":"Zhang","year":"2024","journal-title":"J. Manuf. Syst."},{"key":"10.1016\/j.engappai.2026.114063_bib50","doi-asserted-by":"crossref","first-page":"110249","DOI":"10.1109\/ACCESS.2019.2933991","article-title":"Dynamics study of straddle-type monorail vehicle with single-axle bogies-based full-scale rigid-flexible coupling dynamic model","volume":"7","author":"Zhou","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2026.114063_bib51","author":"Zhou"},{"key":"10.1016\/j.engappai.2026.114063_bib52","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2025.112620","article-title":"Shimmy vibration control of straddle-type monorail vehicle with time delay compensation based on signal influence of multisource random track surface excitation","volume":"230","author":"Zhou","year":"2025","journal-title":"Mech. Syst. Signal Process."},{"key":"10.1016\/j.engappai.2026.114063_bib53","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1080\/00423114.2023.2211694","article-title":"Shimmy analysis of straddle-type monorail vehicle with single-axle bogies based on factor model","volume":"62","author":"Zhou","year":"2024","journal-title":"Veh. Syst. Dyn."}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626003441?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197626003441?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:26:38Z","timestamp":1777595198000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197626003441"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":53,"alternative-id":["S0952197626003441"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114063","relation":{},"ISSN":["0952-1976"],"issn-type":[{"value":"0952-1976","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Adaptive critical speed prediction for straddle-type monorail operational safety: A meta-learning framework with few-shot deployment","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2026.114063","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":"114063"}}