{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T18:03:36Z","timestamp":1772301816382,"version":"3.50.1"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Scientific Research Fund of Hunan Provincial Education","award":["19C1472"],"award-info":[{"award-number":["19C1472"]}]},{"name":"Scientific Research Fund of Hunan Provincial Education","award":["17C1266"],"award-info":[{"award-number":["17C1266"]}]},{"name":"Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province","award":["ZNKZ2018-5"],"award-info":[{"award-number":["ZNKZ2018-5"]}]},{"name":"Key Scientific Research Projects of Huaihua University","award":["HHUY2019-08"],"award-info":[{"award-number":["HHUY2019-08"]}]},{"name":"Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities"},{"name":"Constructing Program of the Key Discipline in Huaihua University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.2983588","type":"journal-article","created":{"date-parts":[[2020,3,26]],"date-time":"2020-03-26T19:50:11Z","timestamp":1585252211000},"page":"61915-61928","source":"Crossref","is-referenced-by-count":46,"title":["Hybrid Method for Short-Term Time Series Forecasting Based on EEMD"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9061-3374","authenticated-orcid":false,"given":"Yujun","family":"Yang","sequence":"first","affiliation":[]},{"given":"Yimei","family":"Yang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2908387"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.23919\/VLSIC.2019.8778193"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/MECO.2017.7977207"},{"key":"ref32","first-page":"1","article-title":"A generalized net model of the deep learning neural network","author":"sotirov","year":"2018","journal-title":"Proc Adv Neural Netw Res Appl"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCE-Berlin.2018.8576235"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1098\/rspa.1998.0193"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICSGEA.2019.00058"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2944672"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCABS.2018.8541985"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"34i","DOI":"10.1093\/jmicro\/dfw068","article-title":"PM-05 Applications of a particle extraction method with deep neural networks using improved auto-encoders to biological ultra-thin section images","volume":"65","author":"tezuka","year":"2016","journal-title":"Microscopy"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1049\/oap-cired.2017.0776"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICASERT.2019.8934638"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2015.2390226"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TEMC.2019.2942435"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1046\/j.1365-8711.1999.02824.x"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPS.2011.2155093"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1049\/el:19920172"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2019.2930583"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1049\/cp.2014.0564"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IC3INA.2015.7377765"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2791507"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TLA.2018.8291461"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-004-0413-4"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2014.2337273"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2014.09.003"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2003.09.015"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2900563"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2012.10.014"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMAG.2015.2482964"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2016.2517622"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2015.04.065"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TNS.2012.2227800"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1109\/TSMCC.2011.2170420","article-title":"Machine learning in financial crisis prediction: A survey","volume":"42","author":"lin","year":"2012","journal-title":"IEEE Trans Syst Man Cybern C (Appl Rev )"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1142\/S0129183117500280"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2011.2169426"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2017.04.005"},{"key":"ref48","first-page":"1841","article-title":"Short-term wind power prediction based on empirical mode decomposition and extreme learning machine","volume":"13","author":"zhongda","year":"2018","journal-title":"J Elect Eng Technol"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ISPCC.2017.8269651"},{"key":"ref47","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1002\/we.2422","article-title":"A prediction approach using ensemble empirical mode decomposition-permutation entropy and regularized extreme learning machine for short-term wind speed","volume":"23","author":"zhongda","year":"2020","journal-title":"Wind Energy"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/SIU.2014.6830341"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1142\/S1793536909000047"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICDS47004.2019.8942294"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2406759"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2019.8898978"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/INISTA.2015.7276742"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2925046"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CTCEEC.2017.8455083"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09047933.pdf?arnumber=9047933","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T15:57:17Z","timestamp":1642003037000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9047933\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":48,"URL":"https:\/\/doi.org\/10.1109\/access.2020.2983588","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}