{"id":"https://openalex.org/W3210442909","doi":"https://doi.org/10.1109/dsaa53316.2021.9564184","title":"Extracting Invariant Features for Predicting State of Health of Batteries in Hybrid Energy Buses","display_name":"Extracting Invariant Features for Predicting State of Health of Batteries in Hybrid Energy Buses","publication_year":2021,"publication_date":"2021-10-06","ids":{"openalex":"https://openalex.org/W3210442909","doi":"https://doi.org/10.1109/dsaa53316.2021.9564184","mag":"3210442909"},"language":"en","primary_location":{"id":"doi:10.1109/dsaa53316.2021.9564184","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa53316.2021.9564184","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)","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/A5045149972","display_name":"Mohammed Ghaith Altarabichi","orcid":"https://orcid.org/0000-0002-6040-2269"},"institutions":[{"id":"https://openalex.org/I746986","display_name":"Halmstad University","ror":"https://ror.org/03h0qfp10","country_code":"SE","type":"education","lineage":["https://openalex.org/I746986"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Mohammed Ghaith Altarabichi","raw_affiliation_strings":["Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden"],"affiliations":[{"raw_affiliation_string":"Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden","institution_ids":["https://openalex.org/I746986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007440397","display_name":"Yuantao Fan","orcid":"https://orcid.org/0000-0002-3034-6630"},"institutions":[{"id":"https://openalex.org/I746986","display_name":"Halmstad University","ror":"https://ror.org/03h0qfp10","country_code":"SE","type":"education","lineage":["https://openalex.org/I746986"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Yuantao Fan","raw_affiliation_strings":["Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden"],"affiliations":[{"raw_affiliation_string":"Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden","institution_ids":["https://openalex.org/I746986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065509988","display_name":"Sepideh Pashami","orcid":"https://orcid.org/0000-0003-3272-4145"},"institutions":[{"id":"https://openalex.org/I746986","display_name":"Halmstad University","ror":"https://ror.org/03h0qfp10","country_code":"SE","type":"education","lineage":["https://openalex.org/I746986"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sepideh Pashami","raw_affiliation_strings":["Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden"],"affiliations":[{"raw_affiliation_string":"Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden","institution_ids":["https://openalex.org/I746986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022044150","display_name":"Peyman Sheikholharam Mashhadi","orcid":"https://orcid.org/0000-0002-0051-0954"},"institutions":[{"id":"https://openalex.org/I746986","display_name":"Halmstad University","ror":"https://ror.org/03h0qfp10","country_code":"SE","type":"education","lineage":["https://openalex.org/I746986"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Peyman Sheikholharam Mashhadi","raw_affiliation_strings":["Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden"],"affiliations":[{"raw_affiliation_string":"Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden","institution_ids":["https://openalex.org/I746986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032811876","display_name":"S\u0142awomir Nowaczyk","orcid":"https://orcid.org/0000-0002-7796-5201"},"institutions":[{"id":"https://openalex.org/I746986","display_name":"Halmstad University","ror":"https://ror.org/03h0qfp10","country_code":"SE","type":"education","lineage":["https://openalex.org/I746986"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Slawomir Nowaczyk","raw_affiliation_strings":["Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden"],"affiliations":[{"raw_affiliation_string":"Center for Applied Intelligent Systems Research (CAISR), Halmstad University, Halmstad, Sweden","institution_ids":["https://openalex.org/I746986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5045149972"],"corresponding_institution_ids":["https://openalex.org/I746986"],"apc_list":null,"apc_paid":null,"fwci":0.5499,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66279617,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.9866999983787537,"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9855999946594238,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/unavailability","display_name":"Unavailability","score":0.9158297777175903},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6735792756080627},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.5520437955856323},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5336946249008179},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4932031035423279},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.47363534569740295},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.4413056969642639},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.43365728855133057},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.35304754972457886},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.260936439037323},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20651453733444214}],"concepts":[{"id":"https://openalex.org/C2780505938","wikidata":"https://www.wikidata.org/wiki/Q17093282","display_name":"Unavailability","level":2,"score":0.9158297777175903},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6735792756080627},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.5520437955856323},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5336946249008179},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4932031035423279},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.47363534569740295},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.4413056969642639},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.43365728855133057},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.35304754972457886},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.260936439037323},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20651453733444214},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsaa53316.2021.9564184","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsaa53316.2021.9564184","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1514048016","https://openalex.org/W1593532658","https://openalex.org/W1964176984","https://openalex.org/W2017136542","https://openalex.org/W2101234009","https://openalex.org/W2140730562","https://openalex.org/W2162651021","https://openalex.org/W2201263372","https://openalex.org/W2215994231","https://openalex.org/W2799462250","https://openalex.org/W2890169947","https://openalex.org/W2891765548","https://openalex.org/W2980420373","https://openalex.org/W3016824580","https://openalex.org/W3126452185","https://openalex.org/W3127344709","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W2113981829","https://openalex.org/W2112959154","https://openalex.org/W2106492215","https://openalex.org/W2326694407","https://openalex.org/W2082859007","https://openalex.org/W2378719652","https://openalex.org/W2115729582","https://openalex.org/W2164831575","https://openalex.org/W2094658154","https://openalex.org/W2370837632"],"abstract_inverted_index":{"Batteries":[0],"are":[1,151,263],"a":[2,130,174,188,205,215,240,277],"safety-critical":[3],"and":[4,60,78,118,224],"the":[5,15,18,27,41,44,54,58,141,193,221,229,254,281],"most":[6],"expensive":[7],"component":[8],"for":[9,52,85,103,114,167,181],"electric":[10],"vehicles":[11],"(EVs).":[12],"To":[13],"ensure":[14],"reliability":[16],"of":[17,29,31,43,57,89,100,111,120,143,176,210,236,242,280],"EVs":[19],"in":[20,71,107,186,231,253],"operation,":[21],"it":[22],"is":[23,37,137,146,212],"crucial":[24],"to":[25,40,67,127,134,147,178,191,233,276,285],"monitor":[26],"state":[28],"health":[30],"those":[32],"batteries.":[33],"Monitoring":[34],"their":[35],"deterioration":[36],"also":[38],"relevant":[39],"sustainability":[42],"transport":[45],"solutions,":[46],"through":[47],"creating":[48],"an":[49,161,286],"efficient":[50],"strategy":[51],"utilizing":[53],"remaining":[55],"capacity":[56],"battery":[59],"its":[61],"second":[62],"life.":[63],"Electric":[64],"buses,":[65],"similar":[66],"other":[68],"EVs,":[69],"come":[70],"many":[72],"different":[73,76,95,154,196,261,266],"variants,":[74],"including":[75],"configurations":[77],"operating":[79],"conditions.":[80],"Developing":[81],"new":[82,135],"degradation":[83],"models":[84,284],"each":[86,202],"existing":[87],"combination":[88],"settings":[90,136],"can":[91],"become":[92],"challenging":[93],"from":[94],"perspectives":[96],"such":[97,187],"as":[98,190],"unavailability":[99],"failure":[101],"data":[102,112],"novel":[104],"settings,":[105],"heterogeneity":[106],"data,":[108],"low":[109],"amount":[110],"available":[113],"less":[115],"popular":[116],"configurations,":[117],"lack":[119],"sufficient":[121],"engineering":[122],"knowledge.":[123],"Therefore,":[124],"being":[125,204],"able":[126],"automatically":[128],"transfer":[129,249],"machine":[131,183,282],"learning":[132,184,250,283],"model":[133],"crucial.":[138],"More":[139],"concretely,":[140],"aim":[142],"this":[144,157],"work":[145],"extract":[148],"features":[149,170,177,262,274],"that":[150,172,271],"invariant":[152,169,273],"across":[153,195],"settings.":[155,197,267],"In":[156],"study,":[158],"we":[159,258],"propose":[160],"evolutionary":[162],"method,":[163],"called":[164],"genetic":[165],"algorithm":[166],"domain":[168,225],"(GADIF),":[171],"selects":[173],"set":[175],"be":[179],"used":[180],"training":[182],"models,":[185],"way":[189],"maximize":[192],"invariance":[194],"A":[198],"Genetic":[199],"Algorithm,":[200],"with":[201,214],"chromosome":[203],"binary":[206],"vector":[207],"signaling":[208],"selection":[209,245],"features,":[211],"equipped":[213],"specific":[216],"fitness":[217],"function":[218],"encompassing":[219],"both":[220],"task":[222],"performance":[223],"shift.":[226],"We":[227],"contrast":[228],"performance,":[230],"migrating":[232],"unseen":[234,287],"domains,":[235],"our":[237],"method":[238],"against":[239],"number":[241],"classical":[243],"feature":[244],"methods":[246],"without":[247],"any":[248],"mechanism.":[251],"Moreover,":[252],"experimental":[255],"result":[256],"section,":[257],"analyze":[259],"how":[260],"selected":[264],"under":[265],"The":[268],"results":[269],"show":[270],"using":[272],"leads":[275],"better":[278],"generalization":[279],"domain.":[288]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
