{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T18:09:02Z","timestamp":1778263742492,"version":"3.51.4"},"reference-count":41,"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":[{"name":"National Key R&D Program of China","award":["2016YFB1200100"],"award-info":[{"award-number":["2016YFB1200100"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2925468","type":"journal-article","created":{"date-parts":[[2019,6,27]],"date-time":"2019-06-27T20:03:36Z","timestamp":1561665816000},"page":"87178-87191","source":"Crossref","is-referenced-by-count":361,"title":["A Neural-Network-Based Method for RUL Prediction and SOH Monitoring of Lithium-Ion Battery"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8664-2236","authenticated-orcid":false,"given":"Jiantao","family":"Qu","sequence":"first","affiliation":[]},{"given":"Feng","family":"Liu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6131-2599","authenticated-orcid":false,"given":"Yuxiang","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Jiaming","family":"Fan","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TENCON.2016.7848384"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.aqpro.2015.02.097"},{"key":"ref33","article-title":"Feed-forward networks with attention can solve some long-term memory problems","author":"raffel","year":"2015","journal-title":"arXiv 1512 08756"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-018-1176-4"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2832053"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2865280"},{"key":"ref37","first-page":"70","article-title":"Medium term electricity load forecasting based on CEEMDAN, permutation entropy and ESN with leaky integrator neurons","volume":"19","author":"li","year":"2015","journal-title":"Elect Mach Control"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2014.06.009"},{"key":"ref35","article-title":"Particle swarm optimization","author":"kennedy","year":"2011","journal-title":"Encyclopedia of Machine Learning"},{"key":"ref34","first-page":"1942","article-title":"Particle swarm optimization","author":"kennedy","year":"2002","journal-title":"Proc Int Conf Neural Networks (ICNN)"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.microrel.2015.02.025"},{"key":"ref40","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","volume":"1","author":"han","year":"2015","journal-title":"Proc 28th Int Conf Neural Inf Process Syst"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2014.08.006"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2013.12.010"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2013.2259193"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2015.2418294"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpowsour.2016.08.054"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2017.11.020"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2014.2385069"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICPHM.2016.7542847"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.microrel.2017.12.036"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2018.2805189"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2018.2796723"},{"key":"ref27","doi-asserted-by":"crossref","DOI":"10.36001\/phmconf.2010.v2i1.1896","article-title":"An adaptive recurrent neural network for remaining useful life prediction of lithium-ion batteries","author":"liu","year":"2010"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2017.01.121"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3390\/en6094682"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/MIM.2008.4579269"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/PHM.2014.6988190"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/MSPEC.2018.8302385"},{"key":"ref2","first-page":"1759","article-title":"A data-driven bias-correction-method-based lithium-ion battery modeling approach for electric vehicle applications","volume":"52","author":"gong","year":"2016","journal-title":"IEEE Trans Ind Appl"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2015.2451074"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MPE.2017.2708812"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.microrel.2016.07.151"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2016.10.026"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2018.2808918"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpowsour.2012.11.146"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.jappgeo.2012.05.002"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpowsour.2013.02.012"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2858856"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICPHM.2017.7998297"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08747502.pdf?arnumber=8747502","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,20]],"date-time":"2024-07-20T09:55:01Z","timestamp":1721469301000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8747502\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":41,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2925468","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}