{"id":"https://openalex.org/W3187996717","doi":"https://doi.org/10.1109/icphm51084.2021.9486674","title":"A Multiscale Entropy-Based Long Short Term Memory Model for Lithium-Ion Battery Prognostics","display_name":"A Multiscale Entropy-Based Long Short Term Memory Model for Lithium-Ion Battery Prognostics","publication_year":2021,"publication_date":"2021-06-07","ids":{"openalex":"https://openalex.org/W3187996717","doi":"https://doi.org/10.1109/icphm51084.2021.9486674","mag":"3187996717"},"language":"en","primary_location":{"id":"doi:10.1109/icphm51084.2021.9486674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icphm51084.2021.9486674","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Prognostics and Health Management (ICPHM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010860229","display_name":"Alireza Namdari","orcid":"https://orcid.org/0000-0002-1776-5179"},"institutions":[{"id":"https://openalex.org/I19833938","display_name":"Western New England University","ror":"https://ror.org/007cnf143","country_code":"US","type":"education","lineage":["https://openalex.org/I19833938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alireza Namdari","raw_affiliation_strings":["Management Western New England University, Springfield, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Management Western New England University, Springfield, MA, USA","institution_ids":["https://openalex.org/I19833938"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100696183","display_name":"Zhaojun Li","orcid":"https://orcid.org/0000-0002-2755-7592"},"institutions":[{"id":"https://openalex.org/I19833938","display_name":"Western New England University","ror":"https://ror.org/007cnf143","country_code":"US","type":"education","lineage":["https://openalex.org/I19833938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaojun Steven Li","raw_affiliation_strings":["Management Western New England University, Springfield, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Management Western New England University, Springfield, MA, USA","institution_ids":["https://openalex.org/I19833938"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1158,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.76986768,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10663","display_name":"Advanced Battery Technologies Research","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10018","display_name":"Advancements in Battery Materials","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prognostics","display_name":"Prognostics","score":0.9517431259155273},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5992151498794556},{"id":"https://openalex.org/keywords/battery","display_name":"Battery (electricity)","score":0.5725031495094299},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5276790261268616},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.4590661823749542},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.451874703168869},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.4485074281692505},{"id":"https://openalex.org/keywords/lithium-ion-battery","display_name":"Lithium-ion battery","score":0.43540748953819275},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2801576256752014},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2755403518676758},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20437633991241455},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.16713804006576538},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.08248341083526611}],"concepts":[{"id":"https://openalex.org/C129364497","wikidata":"https://www.wikidata.org/wiki/Q3042561","display_name":"Prognostics","level":2,"score":0.9517431259155273},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5992151498794556},{"id":"https://openalex.org/C555008776","wikidata":"https://www.wikidata.org/wiki/Q267298","display_name":"Battery (electricity)","level":3,"score":0.5725031495094299},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5276790261268616},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.4590661823749542},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.451874703168869},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.4485074281692505},{"id":"https://openalex.org/C2779197387","wikidata":"https://www.wikidata.org/wiki/Q2822895","display_name":"Lithium-ion battery","level":4,"score":0.43540748953819275},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2801576256752014},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2755403518676758},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20437633991241455},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.16713804006576538},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.08248341083526611},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icphm51084.2021.9486674","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icphm51084.2021.9486674","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Prognostics and Health Management (ICPHM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8399999737739563,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1972985055","https://openalex.org/W2022736603","https://openalex.org/W2040861280","https://openalex.org/W2055942136","https://openalex.org/W2069076542","https://openalex.org/W2078279667","https://openalex.org/W2114869648","https://openalex.org/W2147023814","https://openalex.org/W2295405103","https://openalex.org/W2507528849","https://openalex.org/W2514013593","https://openalex.org/W2560706027","https://openalex.org/W2742338241","https://openalex.org/W2744550671","https://openalex.org/W2790625295","https://openalex.org/W2795701208","https://openalex.org/W2907460853","https://openalex.org/W2949687910","https://openalex.org/W2962135525","https://openalex.org/W2999951339","https://openalex.org/W3000815944","https://openalex.org/W3013372615","https://openalex.org/W3046667168","https://openalex.org/W3084145441","https://openalex.org/W3122086316","https://openalex.org/W3140993386","https://openalex.org/W4253362561"],"related_works":["https://openalex.org/W2310476526","https://openalex.org/W3213192587","https://openalex.org/W2144291498","https://openalex.org/W2535730979","https://openalex.org/W2030958945","https://openalex.org/W2370073012","https://openalex.org/W4386567722","https://openalex.org/W2168646784","https://openalex.org/W2466930957","https://openalex.org/W2994927414"],"abstract_inverted_index":{"Data-driven":[0],"methods":[1,25],"for":[2,53,110],"battery":[3,16,40,68,94,123],"prognostics":[4],"aim":[5],"to":[6,12,65,117,122],"capture":[7],"information":[8,44,148],"from":[9,43,149],"past":[10,101],"data":[11,21,69],"predict":[13],"the":[14,36,39,67,88,99,112,118,125,137],"future":[15],"performance.":[17],"Large":[18],"amount":[19],"of":[20,92],"required":[22],"in":[23,38,106,129,142],"these":[24],"can":[26,46],"be":[27,47],"further":[28],"complicated":[29],"by":[30],"noises.":[31],"Coarse-graining":[32],"technique":[33],"may":[34],"reduce":[35],"noises":[37],"data.":[41],"Entropy,":[42],"viewpoint,":[45],"used":[48],"as":[49,103],"an":[50],"input":[51,104],"variable":[52],"prognostics.":[54],"Long":[55],"Short":[56],"Term":[57],"Memory":[58],"(LSTM)":[59],"algorithm":[60],"is":[61,72],"a":[62,107],"good":[63],"candidate":[64],"fit":[66],"since":[70,132],"it":[71,133],"compatible":[73],"with":[74],"numerical":[75],"dependent":[76],"variables":[77,105],"and":[78,98,145],"yields":[79],"great":[80],"generalization":[81],"ability.":[82],"In":[83],"this":[84],"paper,":[85],"we":[86],"utilize":[87],"multiscale":[89],"Shannon":[90],"entropy":[91],"lithium-ion":[93],"coarse-grained":[95],"voltage":[96,143],"sequences":[97,144],"actual":[100],"capacities":[102,150],"LSTM":[108],"model":[109,127],"predicting":[111],"next-cycle":[113],"capacities.":[114],"As":[115],"compared":[116],"traditional":[119],"data-driven":[120],"approaches":[121],"prognostics,":[124],"proposed":[126],"results":[128],"high":[130],"accuracy":[131],"takes":[134],"into":[135],"account":[136],"multiple":[138],"time":[139],"scales":[140],"inherent":[141],"stores":[146],"key":[147],"over":[151],"charge/discharge":[152],"cycles.":[153]},"counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}