{"id":"https://openalex.org/W4417470545","doi":"https://doi.org/10.1109/tce.2025.3645845","title":"A Novel Multilayer-Perceptron-Based Electronic Nose Technology for Automotive Interior Odor Classification","display_name":"A Novel Multilayer-Perceptron-Based Electronic Nose Technology for Automotive Interior Odor Classification","publication_year":2025,"publication_date":"2025-12-18","ids":{"openalex":"https://openalex.org/W4417470545","doi":"https://doi.org/10.1109/tce.2025.3645845"},"language":null,"primary_location":{"id":"doi:10.1109/tce.2025.3645845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2025.3645845","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Consumer Electronics","raw_type":"journal-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/A5111359722","display_name":"Jinziyuan Lv","orcid":"https://orcid.org/0009-0002-7967-3066"},"institutions":[{"id":"https://openalex.org/I182722699","display_name":"Shenzhen Polytechnic University","ror":"https://ror.org/00d2w9g53","country_code":"CN","type":"education","lineage":["https://openalex.org/I182722699"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinziyuan Lv","raw_affiliation_strings":["Institute of Intelligence Science and Engineering, Shenzhen Polytechnic University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligence Science and Engineering, Shenzhen Polytechnic University, Shenzhen, China","institution_ids":["https://openalex.org/I182722699"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100759169","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0002-6847-8452"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Wang","raw_affiliation_strings":["School of Electrical and Control Engineering, North China University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Control Engineering, North China University of Technology, Beijing, China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011900340","display_name":"Zhijiang Lou","orcid":"https://orcid.org/0000-0003-3912-904X"},"institutions":[{"id":"https://openalex.org/I182722699","display_name":"Shenzhen Polytechnic University","ror":"https://ror.org/00d2w9g53","country_code":"CN","type":"education","lineage":["https://openalex.org/I182722699"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijiang Lou","raw_affiliation_strings":["Institute of Intelligence Science and Engineering, Shenzhen Polytechnic University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligence Science and Engineering, Shenzhen Polytechnic University, Shenzhen, China","institution_ids":["https://openalex.org/I182722699"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017461058","display_name":"Shan Lu","orcid":"https://orcid.org/0000-0001-9357-9821"},"institutions":[{"id":"https://openalex.org/I182722699","display_name":"Shenzhen Polytechnic University","ror":"https://ror.org/00d2w9g53","country_code":"CN","type":"education","lineage":["https://openalex.org/I182722699"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Lu","raw_affiliation_strings":["Institute of Intelligence Science and Engineering, Shenzhen Polytechnic University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligence Science and Engineering, Shenzhen Polytechnic University, Shenzhen, China","institution_ids":["https://openalex.org/I182722699"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5111359722"],"corresponding_institution_ids":["https://openalex.org/I182722699"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40210751,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"72","issue":"1","first_page":"120","last_page":"133"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T12321","display_name":"Insect Pheromone Research and Control","score":0.006399999838322401,"subfield":{"id":"https://openalex.org/subfields/1109","display_name":"Insect Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10461","display_name":"Gas Sensing Nanomaterials and Sensors","score":0.003100000089034438,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/electronic-nose","display_name":"Electronic nose","score":0.8220999836921692},{"id":"https://openalex.org/keywords/odor","display_name":"Odor","score":0.5343999862670898},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4975999891757965},{"id":"https://openalex.org/keywords/hinge-loss","display_name":"Hinge loss","score":0.45649999380111694},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.42739999294281006},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4077000021934509}],"concepts":[{"id":"https://openalex.org/C23895516","wikidata":"https://www.wikidata.org/wiki/Q550092","display_name":"Electronic nose","level":2,"score":0.8220999836921692},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5674999952316284},{"id":"https://openalex.org/C2778916471","wikidata":"https://www.wikidata.org/wiki/Q485537","display_name":"Odor","level":2,"score":0.5343999862670898},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.527400016784668},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4975999891757965},{"id":"https://openalex.org/C39891107","wikidata":"https://www.wikidata.org/wiki/Q5767098","display_name":"Hinge loss","level":3,"score":0.45649999380111694},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.4383000135421753},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.42739999294281006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4077000021934509},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4059000015258789},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.3434999883174896},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.2696000039577484},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2563000023365021},{"id":"https://openalex.org/C52121051","wikidata":"https://www.wikidata.org/wiki/Q43193","display_name":"Truck","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tce.2025.3645845","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2025.3645845","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Consumer Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2608898116","https://openalex.org/W2735866065","https://openalex.org/W2782136875","https://openalex.org/W2803781749","https://openalex.org/W2884853356","https://openalex.org/W2886499297","https://openalex.org/W2889874857","https://openalex.org/W2921480582","https://openalex.org/W2955425764","https://openalex.org/W2963251075","https://openalex.org/W2964054038","https://openalex.org/W3013434849","https://openalex.org/W3033266910","https://openalex.org/W3036357941","https://openalex.org/W3046260628","https://openalex.org/W3092760571","https://openalex.org/W3094124502","https://openalex.org/W3094575529","https://openalex.org/W3098896944","https://openalex.org/W3129098724","https://openalex.org/W3134020713","https://openalex.org/W4205459042","https://openalex.org/W4308560680","https://openalex.org/W4320477389","https://openalex.org/W4327921942","https://openalex.org/W4367671934","https://openalex.org/W4385649027","https://openalex.org/W4385953641","https://openalex.org/W4386783371","https://openalex.org/W4386913524","https://openalex.org/W4388037576","https://openalex.org/W4391896179","https://openalex.org/W4395677719","https://openalex.org/W4401154718","https://openalex.org/W4402026346","https://openalex.org/W4402077967","https://openalex.org/W4404199316","https://openalex.org/W4409561289"],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"car":[3,48,101],"interior":[4,49,102],"odor":[5,14,50,103],"detection":[6,15],"has":[7],"become":[8],"a":[9,44,55],"research":[10],"hotspot,":[11],"the":[12,25,64,68,73,88,91,100,111,119],"traditional":[13,120],"method":[16,53,113],"is":[17,76],"based":[18,42],"on":[19,43],"manual":[20],"detection,":[21],"which":[22],"cannot":[23],"handle":[24],"large":[26],"data":[27,104],"volume,":[28],"multi-classification,":[29],"and":[30,75,144],"class":[31,69],"imbalance":[32,70],"issues.":[33],"As":[34],"such,":[35],"we":[36],"propose":[37],"an":[38,79],"electronic":[39,107],"nose":[40,108],"system":[41],"multi-layer":[45,92],"perceptron":[46,93],"for":[47],"classification.":[51],"The":[52,96],"contains":[54],"new":[56],"dynamic":[57,81],"hybrid":[58],"loss":[59,125,129,132,135,138],"function":[60],"that":[61,110],"can":[62],"adjust":[63,87],"weights":[65],"according":[66],"to":[67,85],"characteristics":[71],"of":[72,90,99],"data,":[74],"combined":[77],"with":[78],"improved":[80],"whale":[82],"optimization":[83],"algorithm":[84],"dynamically":[86],"parameters":[89],"(MLP)":[94],"network.":[95],"testing":[97],"results":[98],"detected":[105],"by":[106],"demonstrates":[109],"proposed":[112],"achieves":[114],"higher":[115],"classification":[116],"accuracy":[117],"than":[118],"methods":[121],"such":[122],"as":[123],"cross-entropy":[124,128],"(CE),":[126],"weighted":[127],"(WCE),":[130],"focal":[131],"(FL),":[133],"dice":[134],"(DL),":[136],"hinge":[137],"(HL),":[139],"convolutional":[140],"neural":[141],"networks":[142,148],"(CNN)":[143],"long":[145],"short-term":[146],"memory":[147],"(LSTM).":[149]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-12-18T00:00:00"}