{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T07:58:37Z","timestamp":1774166317684,"version":"3.50.1"},"reference-count":33,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/OAPA.html"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1704158"],"award-info":[{"award-number":["U1704158"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1604154"],"award-info":[{"award-number":["U1604154"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11702087"],"award-info":[{"award-number":["11702087"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2016T90944"],"award-info":[{"award-number":["2016T90944"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009555","name":"Henan Normal University","doi-asserted-by":"publisher","award":["14YQ007"],"award-info":[{"award-number":["14YQ007"]}],"id":[{"id":"10.13039\/100009555","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2018.2890693","type":"journal-article","created":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T19:48:17Z","timestamp":1546372097000},"page":"9515-9530","source":"Crossref","is-referenced-by-count":243,"title":["Imbalanced Fault Diagnosis of Rolling Bearing Based on Generative Adversarial Network: A Comparative Study"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5335-9517","authenticated-orcid":false,"given":"Wentao","family":"Mao","sequence":"first","affiliation":[]},{"given":"Yamin","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Ling","family":"Ding","sequence":"additional","affiliation":[]},{"given":"Yuan","family":"Li","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1007\/978-3-662-44851-9_15","article-title":"Optimal thresholding of classifiers to maximize F1 measure","author":"lipton","year":"2014","journal-title":"Proc Eur Conf Mach Learn Knowl Discovery Databases"},{"key":"ref32","first-page":"2489","article-title":"A classification method for imbalance data set based on kernel SMOTE","volume":"37","author":"zeng","year":"2009","journal-title":"ACTA Electron Sinica"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2013.12.003"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2016.2570755"},{"key":"ref10","first-page":"2672","article-title":"Generative adversarial nets","volume":"3","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.364"},{"key":"ref12","author":"fedus","year":"2018","journal-title":"MaskGAN Better text generation via filling in the _____"},{"key":"ref13","author":"radford","year":"2015","journal-title":"Unsupervised Representation learning with deep convolutional generative adversarial networks CoRR"},{"key":"ref14","article-title":"Wasserstein GAN","author":"arjovsky","year":"2017"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.05.024"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2017.8258307"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.07.034"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2018.12.019"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390294"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2016.07.028"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2011.06.010"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2017.08.002"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-011-0465-6"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2018.03.025"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2014.2327589"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2016.06.024"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2007.04.009"},{"key":"ref7","first-page":"414","article-title":"A kernel Fisher linear discriminant analysis approach aiming at imbalanced data set","volume":"23","author":"yin","year":"2010","journal-title":"Pattern Recognit Artif Intell"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref9","first-page":"1783","article-title":"Local clustering ensemble learning method based on improved AdaBoost for rare class analysis","volume":"8","author":"xiang","year":"2012","journal-title":"J Comput Inf Syst"},{"key":"ref1","first-page":"150","article-title":"The imbalanced data problem in the fault diagnosis of rolling bearing","volume":"32","author":"liu","year":"2010","journal-title":"Computing in Science & Eng"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2015.10.025"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2014.01.072"},{"key":"ref21","year":"2018","journal-title":"These Data Comes From Case Western Reserve University Bearing Data Center"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/MMW.2002.1028365"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"836","DOI":"10.1109\/TNNLS.2013.2281839","article-title":"Sparse Bayesian extreme learning machine for multi-classification","volume":"25","author":"luo","year":"2014","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1177\/0954406211423454"},{"key":"ref25","first-page":"49","article-title":"Learning output kernels with block coordinate descent","author":"dinuzzo","year":"2011","journal-title":"Proc 28th Int Conf Mach Learn"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08598736.pdf?arnumber=8598736","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T22:34:56Z","timestamp":1643236496000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8598736\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/access.2018.2890693","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}