{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T15:48:28Z","timestamp":1776181708435,"version":"3.50.1"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,2,1]],"date-time":"2024-02-01T00:00:00Z","timestamp":1706745600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52275129"],"award-info":[{"award-number":["52275129"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangxi Science and Technology Major Project","award":["Guike AA22068001"],"award-info":[{"award-number":["Guike AA22068001"]}]},{"DOI":"10.13039\/501100015401","name":"Key Research and Development Projects of Shaanxi Province","doi-asserted-by":"publisher","award":["2022LL-JB-19"],"award-info":[{"award-number":["2022LL-JB-19"]}],"id":[{"id":"10.13039\/501100015401","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["XZY022022026"],"award-info":[{"award-number":["XZY022022026"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["XZY022021006"],"award-info":[{"award-number":["XZY022021006"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2024,2]]},"DOI":"10.1109\/tits.2023.3316793","type":"journal-article","created":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T17:43:13Z","timestamp":1695836593000},"page":"1787-1796","source":"Crossref","is-referenced-by-count":10,"title":["Graph-Based Model Compression for HSR Bogies Fault Diagnosis at IoT Edge via Adversarial Knowledge Distillation"],"prefix":"10.1109","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1328-2663","authenticated-orcid":false,"given":"Wenqing","family":"Wan","sequence":"first","affiliation":[{"name":"State Key Laboratory for Manufacturing and Systems Engineering, Xi’an Jiaotong University, Xi’an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9805-9849","authenticated-orcid":false,"given":"Jinglong","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Manufacturing and Systems Engineering, Xi’an Jiaotong University, Xi’an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7280-3556","authenticated-orcid":false,"given":"Jingsong","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Traffic and Transportation Engineering, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"issue":"1","key":"ref1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/e23010001","article-title":"A review of intelligent fault diagnosis for high-speed trains: Qualitative approaches","volume":"23","author":"Cheng","year":"2020","journal-title":"Entropy"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ITST.2007.4295927"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2016.2647458"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1177\/0954409714560798"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2015.2444240"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/5030175"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3209332"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3029946"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3102017"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3156281"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3167522"},{"key":"ref12","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.117033","article-title":"GA-GRGAT: A novel deep learning model for high-speed train axle temperature long term forecasting","volume":"202","author":"Man","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3059394"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1016\/j.isatra.2023.04.033","article-title":"MIM-graph: A multi-sensor network approach for fault diagnosis of HSR bogie bearings at the IoT edge via mutual information maximization","volume":"139","author":"Wan","year":"2023","journal-title":"ISA Trans."},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3063497"},{"key":"ref16","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2022.109331","article-title":"A neural network compression method based on knowledge-distillation and parameter quantization for the bearing fault diagnosis","volume":"127","author":"Ji","year":"2022","journal-title":"Appl. Soft Comput."},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2022.3214300"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3097408"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3274481"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2021.3091498"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2023.3258748"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11667"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.neucom.2021.04.139","article-title":"Contrastive adversarial knowledge distillation for deep model compression in time-series regression tasks","volume":"485","author":"Xu","year":"2022","journal-title":"Neurocomputing"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00363"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/339"},{"key":"ref27","article-title":"Do deep nets really need to be deep?","volume-title":"Advances in Neural Information Processing Systems","volume":"27","author":"Ba","year":"2014"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1503.02531"},{"key":"ref29","article-title":"KDGAN: Knowledge distillation with generative adversarial networks","volume-title":"Advances in Neural Information Processing Systems","volume":"31","author":"Wang","year":"2018"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3054830"},{"key":"ref31","article-title":"Hierarchical graph representation learning with differentiable pooling","volume-title":"Advances in Neural Information Processing Systems","volume":"31","author":"Ying","year":"2018"},{"key":"ref32","article-title":"Graph attention networks","author":"Veli\u010dkovi\u0107","year":"2017","journal-title":"arXiv:1710.10903"},{"key":"ref33","article-title":"Inductive representation learning on large graphs","volume-title":"Advances in Neural Information Processing Systems","volume":"30","author":"Hamilton","year":"2017"},{"key":"ref34","article-title":"FitNets: Hints for thin deep nets","author":"Romero","year":"2014","journal-title":"arXiv:1412.6550"},{"key":"ref35","first-page":"2006","article-title":"Feature-map-level online adversarial knowledge distillation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Chung"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441735"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380112"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015628"},{"key":"ref39","article-title":"Training shallow and thin networks for acceleration via knowledge distillation with conditional adversarial networks","author":"Xu","year":"2017","journal-title":"arXiv:1709.00513"},{"key":"ref40","article-title":"Training shallow and thin networks for acceleration via knowledge distillation with conditional adversarial networks","author":"Xu","year":"2017","journal-title":"arXiv:1709.00513"},{"key":"ref41","doi-asserted-by":"crossref","DOI":"10.1016\/j.ymssp.2021.108653","article-title":"The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study","volume":"168","author":"Li","year":"2022","journal-title":"Mech. Syst. Signal Process."},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/PHM-Nanjing52125.2021.9612949"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/10419116\/10265771.pdf?arnumber=10265771","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T02:41:16Z","timestamp":1733884876000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10265771\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2]]},"references-count":42,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tits.2023.3316793","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2]]}}}