{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:17:50Z","timestamp":1740169070663,"version":"3.37.3"},"reference-count":39,"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":["61702070","61672121","61703078"],"award-info":[{"award-number":["61702070","61672121","61703078"]}],"id":[{"id":"10.13039\/501100001809","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.2018.2886752","type":"journal-article","created":{"date-parts":[[2018,12,14]],"date-time":"2018-12-14T21:54:40Z","timestamp":1544824480000},"page":"7368-7380","source":"Crossref","is-referenced-by-count":5,"title":["The Regression Learning of the Imbalanced and Big Data by the Online Mixture Model for the Mach Number Forecasting"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1571-1636","authenticated-orcid":false,"given":"Xiao-Jun","family":"Wang","sequence":"first","affiliation":[]},{"given":"Yan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Ping","family":"Yuan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0129-2231","authenticated-orcid":false,"given":"Chang-Jun","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Lin","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","first-page":"126","article-title":"When networks disagree: Ensemble methods for hybrid neural networks","author":"perrone","year":"2001","journal-title":"Artificial Neural Networks for Speech and Vision"},{"key":"ref38","first-page":"37","article-title":"LS-SVMlab toolbox user’s guide, version 1.8","author":"de brabanter","year":"2011"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007607513941"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/BF00058655"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2014.2346832"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2016.2614923"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2010.01.024"},{"key":"ref36","article-title":"Learning scale-adaptive tight correlation filter for object tracking","author":"zhang","year":"0","journal-title":"IEEE Trans Cybern"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2345390"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1109\/34.709601","article-title":"The random subspace method for constructing decision forests","volume":"20","author":"ho","year":"1998","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2014.2350953"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/2976744"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/37.103359"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s11432-017-9095-7"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.cja.2014.12.027"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1177\/0954410011400127"},{"key":"ref16","first-page":"500","article-title":"Steady flow quality assessment of a modified transonic wind tunnel","volume":"20","author":"amiri","year":"2013","journal-title":"Sci Iranica"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s00348-015-2016-5"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2014.130708"},{"key":"ref19","first-page":"1494","article-title":"Wind tunnel Mach number prediction model based on random forest","volume":"37","author":"wang","year":"2016","journal-title":"Acta Aeronautica et Astronautica Sinica"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TIA.2016.2533599"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2441735"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2018.04.014"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2708506"},{"key":"ref6","first-page":"103","article-title":"Early active learning with pairwise constraint for person re-identification","author":"liu","year":"2017","journal-title":"Proc ECML\/PKDD"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00892"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2728531"},{"article-title":"3D data management: Controlling data volume, velocity and variety","year":"2001","author":"laney","key":"ref8"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-017-5202-z"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2016.06.028"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2015.2507658"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-014-0781-x"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TAES.2015.150100"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2016.05.001"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)AS.1943-5525.0000719"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2016.2598228"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2016.27"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2006.17"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08576504.pdf?arnumber=8576504","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T00:13:45Z","timestamp":1643242425000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8576504\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":39,"URL":"https:\/\/doi.org\/10.1109\/access.2018.2886752","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2019]]}}}