{"id":"https://openalex.org/W4210874998","doi":"https://doi.org/10.1109/access.2022.3149523","title":"Prediction of Vehicle Driver\u2019s Facial Air Temperature With SVR, ANN, and GRU","display_name":"Prediction of Vehicle Driver\u2019s Facial Air Temperature With SVR, ANN, and GRU","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4210874998","doi":"https://doi.org/10.1109/access.2022.3149523"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3149523","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3149523","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09706146.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09706146.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001986173","display_name":"Xiaohan Zhang","orcid":"https://orcid.org/0000-0002-3693-8194"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaohan Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100726775","display_name":"Yichun Wang","orcid":"https://orcid.org/0000-0002-5281-8766"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yichun Wang","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5281-8766","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040863314","display_name":"Xinglei He","orcid":"https://orcid.org/0000-0002-5190-9877"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinglei He","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5190-9877","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088645465","display_name":"Hongzeng Ji","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongzeng Ji","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9764-4811","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029768502","display_name":"Yawen Li","orcid":"https://orcid.org/0000-0002-6423-7483"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yawen Li","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6423-7483","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015679766","display_name":"Xiuhui Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuhui Duan","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3056-630X","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035670786","display_name":"Fen Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fen Guo","raw_affiliation_strings":["School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5001986173"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.7889,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.85153062,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"10","issue":null,"first_page":"20212","last_page":"20222"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11109","display_name":"Thermoregulation and physiological responses","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11109","display_name":"Thermoregulation and physiological responses","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11529","display_name":"Refrigeration and Air Conditioning Technologies","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T11861","display_name":"Thermal Regulation in Medicine","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/2706","display_name":"Critical Care and Intensive Care Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.826973557472229},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7046515941619873},{"id":"https://openalex.org/keywords/mean-absolute-error","display_name":"Mean absolute error","score":0.7005404233932495},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.619263768196106},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6024664044380188},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5633941292762756},{"id":"https://openalex.org/keywords/air-temperature","display_name":"Air temperature","score":0.5001277923583984},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.4934903383255005},{"id":"https://openalex.org/keywords/pearson-product-moment-correlation-coefficient","display_name":"Pearson product-moment correlation coefficient","score":0.4626598656177521},{"id":"https://openalex.org/keywords/coefficient-of-determination","display_name":"Coefficient of determination","score":0.4482017159461975},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4463891386985779},{"id":"https://openalex.org/keywords/approximation-error","display_name":"Approximation error","score":0.4175449013710022},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3786536157131195},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23294737935066223},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20919883251190186},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08425375819206238},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.07157406210899353}],"concepts":[{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.826973557472229},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7046515941619873},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.7005404233932495},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.619263768196106},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6024664044380188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5633941292762756},{"id":"https://openalex.org/C2983363897","wikidata":"https://www.wikidata.org/wiki/Q845339","display_name":"Air temperature","level":2,"score":0.5001277923583984},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4934903383255005},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.4626598656177521},{"id":"https://openalex.org/C128990827","wikidata":"https://www.wikidata.org/wiki/Q192830","display_name":"Coefficient of determination","level":2,"score":0.4482017159461975},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4463891386985779},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.4175449013710022},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3786536157131195},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23294737935066223},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20919883251190186},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08425375819206238},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.07157406210899353},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3149523","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3149523","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09706146.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1daab571f2da492493c4ba9d54b26f7f","is_oa":true,"landing_page_url":"https://doaj.org/article/1daab571f2da492493c4ba9d54b26f7f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 20212-20222 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3149523","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3149523","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09706146.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4210874998.pdf","grobid_xml":"https://content.openalex.org/works/W4210874998.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W297158172","https://openalex.org/W1499864241","https://openalex.org/W1537810804","https://openalex.org/W1560724230","https://openalex.org/W1966726259","https://openalex.org/W1985817801","https://openalex.org/W1993163877","https://openalex.org/W2000651380","https://openalex.org/W2064675550","https://openalex.org/W2081038879","https://openalex.org/W2109543790","https://openalex.org/W2115813749","https://openalex.org/W2146292423","https://openalex.org/W2157331557","https://openalex.org/W2159095374","https://openalex.org/W2161920802","https://openalex.org/W2166681263","https://openalex.org/W2267716908","https://openalex.org/W2271840356","https://openalex.org/W2273126748","https://openalex.org/W2342249984","https://openalex.org/W2570605704","https://openalex.org/W2766933588","https://openalex.org/W2783850388","https://openalex.org/W2802436364","https://openalex.org/W2884283518","https://openalex.org/W2945282473","https://openalex.org/W2967059064","https://openalex.org/W2980500585","https://openalex.org/W2984127675","https://openalex.org/W2993639813","https://openalex.org/W3014862332","https://openalex.org/W3034776565","https://openalex.org/W3043715445","https://openalex.org/W3049184217","https://openalex.org/W3082648102","https://openalex.org/W3107335993","https://openalex.org/W3134428061","https://openalex.org/W3181518774","https://openalex.org/W3182209257","https://openalex.org/W3191254781","https://openalex.org/W3210496063","https://openalex.org/W4200568502","https://openalex.org/W4236656556","https://openalex.org/W6629930100","https://openalex.org/W6675354045","https://openalex.org/W6694517276"],"related_works":["https://openalex.org/W2087911819","https://openalex.org/W2136152605","https://openalex.org/W3149853164","https://openalex.org/W2659933339","https://openalex.org/W2971924187","https://openalex.org/W2073947232","https://openalex.org/W2180861079","https://openalex.org/W4312295548","https://openalex.org/W2542451093","https://openalex.org/W4387072315"],"abstract_inverted_index":{"The":[0,120,144,174],"facial":[1,37,245],"air":[2,246],"temperature":[3,24,38,76,247],"has":[4],"a":[5,40],"significant":[6],"impact":[7],"on":[8],"the":[9,35,71,87,100,104,113,116,139,158,170,180,183,186,189,195,202,209,214,222,233,239],"driver\u2019s":[10],"thermal":[11],"comfort.":[12],"Machine":[13],"Learning":[14],"models":[15,30,149,191,218],"have":[16],"been":[17],"proved":[18],"to":[19,33,69,232],"be":[20,206,238],"evidently":[21],"effective":[22],"in":[23,39,92,109,115,157,169,227],"predicting.":[25],"In":[26,96],"this":[27],"study,":[28],"three":[29,148,190],"are":[31,46,103,150,219],"employed":[32],"predict":[34],"drivers\u2019":[36,74,244],"certain":[41],"series":[42],"of":[43,73,107,122,141,146,176,182,216],"vehicles,":[44],"which":[45],"Support":[47],"Vector":[48],"Regression":[49],"(SVR),":[50],"Artificial":[51],"Neural":[52],"Network":[53],"(ANN),":[54],"and":[55,77,89,112,138,162,197,201,211],"Gated":[56],"Recurrent":[57],"Unit":[58],"(GRU)":[59],"respectively.":[60,119],"We":[61],"conduct":[62],"an":[63],"electric":[64],"vehicle":[65,243],"air-conditioning":[66],"system":[67],"experiment":[68],"collect":[70],"datasets":[72,91,102,108,114],"head":[75],"6":[78],"input":[79],"features":[80],"for":[81,242],"model":[82],"training.":[83],"And":[84],"we":[85],"divide":[86],"training":[88],"testing":[90,101],"two":[93,98],"different":[94],"ways.":[95],"these":[97,123,147,217],"ways,":[99],"last":[105,117],"20%":[106],"each":[110],"condition,":[111],"condition":[118],"evaluation":[121],"models\u2019":[124],"performance":[125,181],"is":[126,185,225],"exerted":[127],"with":[128,194],"Root":[129],"Mean":[130,134],"Squared":[131],"Error":[132,136],"(RMSE),":[133],"Absolute":[135],"(MAE),":[137],"coefficient":[140],"determination":[142],"(R2).":[143],"MAE":[145,177],"SVR:":[151,163],"0.8096,":[152],"ANN:":[153,165],"0.4984,":[154],"GRU:":[155,167],"0.7289":[156],"trained":[159,196],"working":[160,172,229],"conditions,":[161],"1.0946,":[164],"0.7878,":[166],"0.7837":[168],"untrained":[171,198],"conditions.":[173,230],"results":[175,234],"show":[178],"that":[179],"ANN":[184,236],"best":[187],"among":[188],"when":[192,221],"tested":[193,223],"test":[199],"datasets,":[200],"same":[203],"conclusion":[204],"can":[205],"got":[207],"from":[208],"R2":[210],"RMSE.":[212],"Moreover,":[213],"accuracies":[215],"lower":[220],"dataset":[224],"collected":[226],"new":[228],"According":[231],"above,":[235],"may":[237],"preferred":[240],"method":[241],"prediction.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2022-02-09T00:00:00"}
