{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T03:13:32Z","timestamp":1783048412816,"version":"3.54.6"},"reference-count":33,"publisher":"IEEE","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872063,61973054"],"award-info":[{"award-number":["61872063,61973054"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,25]]},"DOI":"10.23919\/acc50511.2021.9482728","type":"proceedings-article","created":{"date-parts":[[2021,7,28]],"date-time":"2021-07-28T20:29:16Z","timestamp":1627504156000},"page":"1601-1606","source":"Crossref","is-referenced-by-count":18,"title":["MS-TCN: A Multiscale Temporal Convolutional Network for Fault Diagnosis in Industrial Processes"],"prefix":"10.23919","author":[{"given":"Jiyang","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxuan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianxiong","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianxiao","family":"Zou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shicai","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref33","first-page":"2579","article-title":"Visualizing data using t-SNE","author":"maaten","year":"2008","journal-title":"Journal of Machine Learning Research"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.ces.2008.10.012"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/S0169-7439(00)00058-7"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4471-0347-9"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2016.2582729"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2551940"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2794765"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/pr7030152"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/S0098-1354(02)00093-5"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jprocont.2019.12.002"},{"key":"ref16","first-page":"9","article-title":"An Empirical Exploration of Recurrent Network Architectures","author":"jozefowicz","year":"2015","journal-title":"International Conference on Machine Learning (ICML) 2015"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2582924"},{"key":"ref18","author":"bai","year":"2018","journal-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2947714"},{"key":"ref28","author":"kingma","year":"2017","journal-title":"Adam A method for stochastic optimization"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2006.06.010"},{"key":"ref27","author":"yu","year":"2016","journal-title":"Multi-scale context aggregation by dilated convolutions"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2016.2571680"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2017.2726011"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/0098-1354(93)80018-I"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CDC40024.2019.9029388"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2018.2844805"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.07.008"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2018.2798633"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPWRD.2004.835281"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683634"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.113"},{"key":"ref24","first-page":"9","article-title":"Deep Sparse Rectifier Neural Networks","author":"glorot","year":"2011","journal-title":"the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2011)"},{"key":"ref23","first-page":"9","article-title":"Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks","author":"salimans","year":"2016","journal-title":"Neural Information Processing Systems (NIPS) 2016"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref25","author":"hinton","year":"2012","journal-title":"Improving Neural Networks by Preventing Co-adaptation of Feature Detectors"}],"event":{"name":"2021 American Control Conference (ACC)","location":"New Orleans, LA, USA","start":{"date-parts":[[2021,5,25]]},"end":{"date-parts":[[2021,5,28]]}},"container-title":["2021 American Control Conference (ACC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9482409\/9482614\/09482728.pdf?arnumber=9482728","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,6]],"date-time":"2021-10-06T10:51:08Z","timestamp":1633517468000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9482728\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,25]]},"references-count":33,"URL":"https:\/\/doi.org\/10.23919\/acc50511.2021.9482728","relation":{},"subject":[],"published":{"date-parts":[[2021,5,25]]}}}