{"id":"https://openalex.org/W4396831694","doi":"https://doi.org/10.1186/s40537-024-00926-5","title":"Predicting air quality index using attention hybrid deep learning and quantum-inspired particle swarm optimization","display_name":"Predicting air quality index using attention hybrid deep learning and quantum-inspired particle swarm optimization","publication_year":2024,"publication_date":"2024-05-11","ids":{"openalex":"https://openalex.org/W4396831694","doi":"https://doi.org/10.1186/s40537-024-00926-5"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-024-00926-5","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-00926-5","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00926-5","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00926-5","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065748190","display_name":"Anh Tuan Nguyen","orcid":"https://orcid.org/0000-0002-9235-4759"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Anh Tuan Nguyen","raw_affiliation_strings":["Smart City Engineering, Hanyang University ERICA Campus, 55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Smart City Engineering, Hanyang University ERICA Campus, 55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051472673","display_name":"Duy Hoang Pham","orcid":"https://orcid.org/0000-0003-4442-3390"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Duy Hoang Pham","raw_affiliation_strings":["Smart City Engineering, Hanyang University ERICA Campus, 55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Smart City Engineering, Hanyang University ERICA Campus, 55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077191245","display_name":"Bee Lan Oo","orcid":"https://orcid.org/0000-0003-1660-2121"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Bee Lan Oo","raw_affiliation_strings":["School of Built Environment, University of New South Wales, Kensington, Sydney, NSW, 2052, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Built Environment, University of New South Wales, Kensington, Sydney, NSW, 2052, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088689684","display_name":"Yonghan Ahn","orcid":"https://orcid.org/0000-0002-5542-7314"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yonghan Ahn","raw_affiliation_strings":["Smart City Engineering, Hanyang University ERICA Campus, 55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Smart City Engineering, Hanyang University ERICA Campus, 55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109463772","display_name":"Benson Teck\u2010Heng Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Benson T. H. Lim","raw_affiliation_strings":["School of Built Environment, University of New South Wales, Kensington, Sydney, NSW, 2052, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Built Environment, University of New South Wales, Kensington, Sydney, NSW, 2052, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5065748190"],"corresponding_institution_ids":["https://openalex.org/I4575257"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":10.4483,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.99185134,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"11","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10190","display_name":"Air Quality and Health Impacts","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12095","display_name":"Vehicle emissions and performance","score":0.9746000170707703,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.7856312990188599},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7346318364143372},{"id":"https://openalex.org/keywords/computational-science-and-engineering","display_name":"Computational Science and Engineering","score":0.6456155776977539},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.6003597378730774},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5525771975517273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4469152092933655},{"id":"https://openalex.org/keywords/particle","display_name":"Particle (ecology)","score":0.41523364186286926},{"id":"https://openalex.org/keywords/air-quality-index","display_name":"Air quality index","score":0.4136071503162384},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.4115052819252014},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3478434085845947},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.07297143340110779},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06361645460128784}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.7856312990188599},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7346318364143372},{"id":"https://openalex.org/C68597687","wikidata":"https://www.wikidata.org/wiki/Q362601","display_name":"Computational Science and Engineering","level":2,"score":0.6456155776977539},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.6003597378730774},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5525771975517273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4469152092933655},{"id":"https://openalex.org/C2778517922","wikidata":"https://www.wikidata.org/wiki/Q7140482","display_name":"Particle (ecology)","level":2,"score":0.41523364186286926},{"id":"https://openalex.org/C126314574","wikidata":"https://www.wikidata.org/wiki/Q2364111","display_name":"Air quality index","level":2,"score":0.4136071503162384},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.4115052819252014},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3478434085845947},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.07297143340110779},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06361645460128784},{"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-024-00926-5","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-00926-5","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00926-5","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1a0802314db244109c5f09a150e0b2d7","is_oa":true,"landing_page_url":"https://doaj.org/article/1a0802314db244109c5f09a150e0b2d7","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":"Journal of Big Data, Vol 11, Iss 1, Pp 1-38 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-024-00926-5","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-024-00926-5","pdf_url":"https://journalofbigdata.springeropen.com/counter/pdf/10.1186/s40537-024-00926-5","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4396831694.pdf"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W1566399673","https://openalex.org/W1786686177","https://openalex.org/W2007898191","https://openalex.org/W2009588584","https://openalex.org/W2031183907","https://openalex.org/W2061683845","https://openalex.org/W2064675550","https://openalex.org/W2070586061","https://openalex.org/W2074418717","https://openalex.org/W2161704220","https://openalex.org/W2211192759","https://openalex.org/W2255466643","https://openalex.org/W2295598076","https://openalex.org/W2318977435","https://openalex.org/W2565536624","https://openalex.org/W2573137292","https://openalex.org/W2754663885","https://openalex.org/W2766584915","https://openalex.org/W2769387903","https://openalex.org/W2907910906","https://openalex.org/W2919979744","https://openalex.org/W2921781788","https://openalex.org/W2946446522","https://openalex.org/W3011367647","https://openalex.org/W3017049137","https://openalex.org/W3024620312","https://openalex.org/W3031453720","https://openalex.org/W3039016011","https://openalex.org/W3047026131","https://openalex.org/W3047937490","https://openalex.org/W3092655370","https://openalex.org/W3093869481","https://openalex.org/W3094915885","https://openalex.org/W3110020064","https://openalex.org/W3126075911","https://openalex.org/W3138873693","https://openalex.org/W3154223757","https://openalex.org/W3164032920","https://openalex.org/W3170689778","https://openalex.org/W3197354301","https://openalex.org/W3201502261","https://openalex.org/W3203106094","https://openalex.org/W3210946507","https://openalex.org/W4220998064","https://openalex.org/W4229456413","https://openalex.org/W4280649213","https://openalex.org/W4281261483","https://openalex.org/W4292166922","https://openalex.org/W4293329630","https://openalex.org/W4304607404","https://openalex.org/W4306722794","https://openalex.org/W4309786660","https://openalex.org/W4310004251","https://openalex.org/W4312315814","https://openalex.org/W4313407500","https://openalex.org/W4313422660","https://openalex.org/W4320716715","https://openalex.org/W4321595697","https://openalex.org/W4385245566","https://openalex.org/W4385285815","https://openalex.org/W4388802345","https://openalex.org/W4390383578","https://openalex.org/W6679436768"],"related_works":["https://openalex.org/W4393232657","https://openalex.org/W4390638272","https://openalex.org/W4386596916","https://openalex.org/W3019402777","https://openalex.org/W2031835531","https://openalex.org/W2472237121","https://openalex.org/W4323316863","https://openalex.org/W2388590088","https://openalex.org/W1985111449","https://openalex.org/W1969166468"],"abstract_inverted_index":{"Abstract":[0],"Air":[1,109],"pollution":[2,27,34],"poses":[3],"a":[4,139,253],"significant":[5],"threat":[6],"to":[7,53,65,115,126,162,178,198,231,246],"the":[8,11,30,46,54,76,106,112,123,130,134,146,150,154,164,168,176,180,187,193,200,210,247,269],"health":[9],"of":[10,25,32,45,59,133,153,167,209,257],"environment":[12],"and":[13,35,42,56,95,128,136,173,192,207,215,222,240,261,282,292],"human":[14],"well-being.":[15],"The":[16,117,205,264],"air":[17,26,33,60,100,170,286],"quality":[18,101,171,287],"index":[19,288],"(AQI)":[20],"is":[21,48,279],"an":[22,67],"important":[23],"measure":[24],"that":[28,268],"describes":[29],"degree":[31],"its":[36],"impact":[37],"on":[38,75],"health.":[39],"Therefore,":[40],"accurate":[41],"reliable":[43],"prediction":[44,69,203],"AQI":[47,68,202],"critical":[49],"but":[50],"challenging":[51],"due":[52],"non-linearity":[55],"stochastic":[57],"nature":[58],"particles.":[61],"This":[62,156],"research":[63],"aims":[64],"propose":[66],"hybrid":[70,140,157,271],"deep":[71,141,165,272],"learning":[72,142],"model":[73,125,158,195,212,228,278],"based":[74],"Attention":[77],"Convolutional":[78],"Neural":[79],"Networks":[80],"(ACNN),":[81],"Autoregressive":[82],"Integrated":[83],"Moving":[84],"Average":[85],"(ARIMA),":[86],"Quantum":[87,273],"Particle":[88,275],"Swarm":[89,276],"Optimization":[90,277],"(QPSO)-enhanced-Long":[91],"Short-Term":[92],"Memory":[93],"(LSTM)":[94],"XGBoost":[96,194],"modelling":[97],"techniques.":[98],"Daily":[99],"data":[102,118,135],"were":[103,119,213],"collected":[104],"from":[105],"official":[107],"Seoul":[108],"registry":[110],"for":[111,149,182,185],"period":[113],"2021":[114],"2022.":[116],"first":[120,159],"preprocessed":[121],"through":[122],"ARIMA":[124],"capture":[127],"fit":[129],"linear":[131],"part":[132,152],"followed":[137],"by":[138],"architecture":[143],"developed":[144],"in":[145,234,238,243,284],"pretraining\u2013finetuning":[147],"framework":[148],"non-linear":[151],"data.":[155],"used":[160,175,220],"convolution":[161],"extract":[163],"features":[166],"original":[169],"data,":[172],"then":[174],"QPSO":[177],"optimize":[179],"hyperparameter":[181],"LSTM":[183],"network":[184],"mining":[186],"long-terms":[188],"time":[189],"series":[190],"features,":[191],"was":[196],"adopted":[197],"fine-tune":[199],"final":[201],"model.":[204],"robustness":[206],"reliability":[208],"resulting":[211],"assessed":[214],"compared":[216,245],"with":[217],"other":[218],"widely":[219],"models":[221],"across":[223],"meteorological":[224],"stations.":[225],"Our":[226],"proposed":[227],"achieves":[229],"up":[230],"31.13%":[232],"reduction":[233,237],"MSE,":[235],"19.03%":[236],"MAE":[239],"2%":[241],"improvement":[242],"R-squared":[244],"best":[248],"appropriate":[249],"conventional":[250],"model,":[251],"indicating":[252],"much":[254],"stronger":[255],"magnitude":[256],"relationships":[258],"between":[259],"predicted":[260],"actual":[262],"values.":[263],"overall":[265],"results":[266],"show":[267],"attentive":[270],"inspired":[274],"more":[280],"feasible":[281],"efficient":[283],"predicting":[285],"at":[289],"both":[290],"city-wide":[291],"station-specific":[293],"levels.":[294]},"counts_by_year":[{"year":2026,"cited_by_count":17},{"year":2025,"cited_by_count":34},{"year":2024,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
