{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T17:04:36Z","timestamp":1778605476657,"version":"3.51.4"},"reference-count":61,"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:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71671029"],"award-info":[{"award-number":["71671029"]}],"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.2019.2957062","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T19:03:10Z","timestamp":1575313390000},"page":"178063-178081","source":"Crossref","is-referenced-by-count":44,"title":["Wind Speed Forecasting System Based on the Variational Mode Decomposition Strategy and Immune Selection Multi-Objective Dragonfly Optimization Algorithm"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1850-7697","authenticated-orcid":false,"given":"He","family":"Bo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8638-126X","authenticated-orcid":false,"given":"Xinsong","family":"Niu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9078-7617","authenticated-orcid":false,"given":"Jianzhou","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2015.02.032"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2009.10.028"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1155\/2016\/3205396"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.cnsns.2016.12.017"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3390\/en11040712"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2011.04.019"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2011.04.051"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2013.07.001"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.05.016"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2016.03.103"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/j.apm.2018.10.019"},{"key":"ref61","article-title":"Modelling of carbon price in two real carbon trading markets","volume":"244","author":"hao","year":"2019","journal-title":"J Clean Prod"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2018.07.070"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2017.10.008"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2018.10.129"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/en10091422"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2014.03.033"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2016.08.062"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.eneco.2019.05.026"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TSTE.2019.2890875"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2009.12.013"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2017.01.033"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2017.11.071"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.3390\/su11020526"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1049\/cp.2015.1697"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2013.2288675"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2018.07.032"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1080\/17583004.2019.1577177"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.3390\/app9030423"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2018.12.056"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1038\/nature18848"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.06.094"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1162\/EVCO_a_00109"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-015-1920-1"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/PES.2007.385453"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2018.09.012"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/RTUCON.2014.6998223"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/NAPS.2010.5619586"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2018.07.022"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2013.02.002"},{"key":"ref15","first-page":"906","article-title":"Short-Term load forecasting model for metro power supply system based on echo state neural network","author":"yu","year":"2016","journal-title":"Proc 7th IEEE Int Conf Softw Eng Service Sci (ICSESS)"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2010.08.026"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.econmod.2013.09.033"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2017.09.089"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2018.09.005"},{"key":"ref4","author":"rica","year":"2017","journal-title":"Global Wind Statistics"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2019.04.157"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105587"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.03.097"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2019.01.063"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.03.035"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2574840"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-6105(00)00079-9"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.3390\/en12101931"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.07.024"},{"key":"ref48","article-title":"Integrating grey data preprocessor and deep belief network for day-ahead PV power output forecast","author":"chang","year":"0","journal-title":"EEE Trans Sustain Energy"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2019.111799"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2008.03.014"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2008.09.006"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2010.11.007"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.renene.2015.04.054"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08918258.pdf?arnumber=8918258","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:31:44Z","timestamp":1641987104000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8918258\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":61,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2957062","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}