{"id":"https://openalex.org/W3155393692","doi":"https://doi.org/10.1109/tim.2021.3071313","title":"A Novel Gas Recognition and Concentration Detection Algorithm for Artificial Olfaction","display_name":"A Novel Gas Recognition and Concentration Detection Algorithm for Artificial Olfaction","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3155393692","doi":"https://doi.org/10.1109/tim.2021.3071313","mag":"3155393692"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2021.3071313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3071313","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5100401861","display_name":"Wenwen Zhang","orcid":"https://orcid.org/0009-0004-2927-9735"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenwen Zhang","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100759344","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0001-6983-0123"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086814847","display_name":"Jia Chen","orcid":"https://orcid.org/0000-0002-6350-6610"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jia Chen","raw_affiliation_strings":["Technical University of Munich, Germany, Germany"],"affiliations":[{"raw_affiliation_string":"Technical University of Munich, Germany, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101697697","display_name":"Wenxin Xiao","orcid":"https://orcid.org/0000-0003-2803-0036"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxin Xiao","raw_affiliation_strings":["College of Electronics Engineering and Computer Science, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Electronics Engineering and Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068799172","display_name":"Xiao Bi","orcid":"https://orcid.org/0000-0002-2733-0451"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Xiao Bi","raw_affiliation_strings":["Technical University of Munich, Germany, Germany"],"affiliations":[{"raw_affiliation_string":"Technical University of Munich, Germany, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100401861"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":2.4539,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.88835387,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":1.0,"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":1.0,"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/T10461","display_name":"Gas Sensing Nanomaterials and Sensors","score":0.9986000061035156,"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/T12321","display_name":"Insect Pheromone Research and Control","score":0.9965000152587891,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7048248648643494},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6056578159332275},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6051459312438965},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5157783031463623},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.49711325764656067},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.4943270683288574},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4515296220779419},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4379188120365143},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42714959383010864},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.4207097589969635},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3504255414009094}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7048248648643494},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6056578159332275},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6051459312438965},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5157783031463623},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.49711325764656067},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.4943270683288574},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4515296220779419},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4379188120365143},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42714959383010864},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.4207097589969635},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3504255414009094}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2021.3071313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3071313","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G3478265086","display_name":null,"funder_award_id":"2018YFE0105000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1537357919","https://openalex.org/W1965729970","https://openalex.org/W1971845710","https://openalex.org/W1987289245","https://openalex.org/W1994200344","https://openalex.org/W1998954031","https://openalex.org/W2017060551","https://openalex.org/W2031383529","https://openalex.org/W2034962364","https://openalex.org/W2041105792","https://openalex.org/W2049832930","https://openalex.org/W2059477850","https://openalex.org/W2060063624","https://openalex.org/W2070067489","https://openalex.org/W2074960783","https://openalex.org/W2084812239","https://openalex.org/W2097215200","https://openalex.org/W2129189353","https://openalex.org/W2129591079","https://openalex.org/W2300612839","https://openalex.org/W2325898376","https://openalex.org/W2344475789","https://openalex.org/W2345503480","https://openalex.org/W2469794110","https://openalex.org/W2556701683","https://openalex.org/W2607040660","https://openalex.org/W2608860327","https://openalex.org/W2751146370","https://openalex.org/W2776990447","https://openalex.org/W2821525199","https://openalex.org/W2891658879","https://openalex.org/W2906959764","https://openalex.org/W2948852829","https://openalex.org/W2982187960","https://openalex.org/W6679340442"],"related_works":["https://openalex.org/W2989932438","https://openalex.org/W3081496756","https://openalex.org/W3099765033","https://openalex.org/W3208266890","https://openalex.org/W2996933976","https://openalex.org/W4210794429","https://openalex.org/W2345184372","https://openalex.org/W2767651786","https://openalex.org/W1996541855","https://openalex.org/W2940336242"],"abstract_inverted_index":{"A":[0],"novel":[1],"gas":[2,44,50,60,96,125,210],"recognition":[3,45,85],"and":[4,17,53,94,100,108,144,168,199,218],"concentration":[5,178,211,224],"detection":[6,179,212],"algorithm":[7,37,46,112,173],"consisting":[8],"of":[9,74,87,98,123,225],"a":[10,18,30,75,115,176],"dynamic":[11],"wavelet":[12],"convolutional":[13,76],"neural":[14,23,77,134],"network":[15,24,78,135],"(DWCNN)":[16],"many-to-many":[19,110,208],"long":[20],"short-term":[21],"memory-recurrent":[22],"(LSTM-RNN),":[25],"respectively,":[26],"is":[27,105],"proposed":[28,42,207],"as":[29,70,148],"replacement":[31],"for":[32,189],"the":[33,57,71,84,95,109,120,124,149,172,190,206,215,223],"traditional":[34],"data":[35,62,118],"processing":[36],"in":[38],"artificial":[39],"olfaction.":[40],"The":[41,80,201],"DWCNN":[43],"does":[47],"not":[48],"require":[49],"signal":[51,61],"preprocessing,":[52],"it":[54],"directly":[55],"converts":[56],"raw":[58],"time-domain":[59],"to":[63],"64":[64,66],"*":[65],"2-D":[67],"gray":[68],"images":[69],"input":[72],"layer":[73],"(CNN).":[79],"experiments":[81],"show":[82],"that":[83,171,205],"accuracy":[86],"CO,":[88],"H":[89,101],"<sub":[90,102],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[91,103],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sub>":[92,104],",":[93],"mixture":[97],"CO":[99],"nearly":[106],"100%,":[107],"LSTM-RNN":[111],"requires":[113],"only":[114],"few":[116],"labeled":[117,231],"from":[119],"steady-state":[121],"values":[122],"sensor":[126],"array":[127],"signals.":[128],"In":[129],"addition,":[130],"comparisons":[131],"with":[132],"other":[133],"multilayer":[136],"perceptrons":[137],"(MLPs),":[138],"gated":[139],"recurrent":[140],"unit":[141],"(GRU)":[142],"algorithms,":[143,146],"conventional":[145],"such":[147],"Bayesian":[150],"ridge,":[151],"support":[152],"vector":[153],"machines":[154],"(SVMs),":[155],"decision":[156,165],"tree,":[157],"k-nearest":[158],"neighbor":[159],"(KNN),":[160],"random":[161],"forest,":[162],"AdaBoost,":[163],"gradient-boosting":[164],"tree":[166],"(GBDT),":[167],"bagging,":[169],"revealed":[170],"can":[174,219],"obtain":[175],"higher":[177],"accuracy,":[180],"which":[181],"was":[182],"evaluated":[183],"using":[184,229],"two":[185],"different":[186,226],"kernel":[187,191],"functions":[188],"principal":[192],"component":[193],"analysis":[194],"(KPCA)":[195],"dimensionality":[196],"reduction:":[197],"polynomial":[198],"rbf.":[200],"experimental":[202],"results":[203],"demonstrated":[204],"LSTM":[209],"model":[213],"outperformed":[214],"abovementioned":[216],"algorithms":[217],"more":[220],"accurately":[221],"estimate":[222],"gases":[227],"while":[228],"less":[230],"data.":[232]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
