{"id":"https://openalex.org/W4388096911","doi":"https://doi.org/10.1007/s10489-023-05109-y","title":"A systematic comparison of different machine learning models for the spatial estimation of air pollution","display_name":"A systematic comparison of different machine learning models for the spatial estimation of air pollution","publication_year":2023,"publication_date":"2023-10-31","ids":{"openalex":"https://openalex.org/W4388096911","doi":"https://doi.org/10.1007/s10489-023-05109-y"},"language":"en","primary_location":{"id":"doi:10.1007/s10489-023-05109-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-05109-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-05109-y.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"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":"Applied Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-05109-y.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009965786","display_name":"Elena Cerezuela-Escudero","orcid":"https://orcid.org/0000-0003-0176-7863"},"institutions":[{"id":"https://openalex.org/I79238269","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24","country_code":"ES","type":"education","lineage":["https://openalex.org/I79238269"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Elena Cerezuela-Escudero","raw_affiliation_strings":["Robotics and Technology of Computers Lab (RTC), ETSI Inform\u00e1tica, Universidad de Sevilla, Avd. Reina Mercedes s/n, Sevilla, 41012, Spain"],"raw_orcid":"https://orcid.org/0000-0003-0176-7863","affiliations":[{"raw_affiliation_string":"Robotics and Technology of Computers Lab (RTC), ETSI Inform\u00e1tica, Universidad de Sevilla, Avd. Reina Mercedes s/n, Sevilla, 41012, Spain","institution_ids":["https://openalex.org/I79238269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084461940","display_name":"Juan M. Montes-S\u00e1nchez","orcid":"https://orcid.org/0000-0002-0983-2386"},"institutions":[{"id":"https://openalex.org/I79238269","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24","country_code":"ES","type":"education","lineage":["https://openalex.org/I79238269"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan Manuel Montes-Sanchez","raw_affiliation_strings":["Robotics and Technology of Computers Lab (RTC), ETSI Inform\u00e1tica, Universidad de Sevilla, Avd. Reina Mercedes s/n, Sevilla, 41012, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics and Technology of Computers Lab (RTC), ETSI Inform\u00e1tica, Universidad de Sevilla, Avd. Reina Mercedes s/n, Sevilla, 41012, Spain","institution_ids":["https://openalex.org/I79238269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001923763","display_name":"Juan P. Dominguez\u2010Morales","orcid":"https://orcid.org/0000-0002-5474-107X"},"institutions":[{"id":"https://openalex.org/I79238269","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24","country_code":"ES","type":"education","lineage":["https://openalex.org/I79238269"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan Pedro Dominguez-Morales","raw_affiliation_strings":["Robotics and Technology of Computers Lab (RTC), ETSI Inform\u00e1tica, Universidad de Sevilla, Avd. Reina Mercedes s/n, Sevilla, 41012, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics and Technology of Computers Lab (RTC), ETSI Inform\u00e1tica, Universidad de Sevilla, Avd. Reina Mercedes s/n, Sevilla, 41012, Spain","institution_ids":["https://openalex.org/I79238269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091073021","display_name":"Lourdes Dur\u00e1n-L\u00f3pez","orcid":"https://orcid.org/0000-0002-5849-8003"},"institutions":[{"id":"https://openalex.org/I79238269","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24","country_code":"ES","type":"education","lineage":["https://openalex.org/I79238269"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Lourdes Duran-Lopez","raw_affiliation_strings":["Robotics and Technology of Computers Lab (RTC), ETSI Inform\u00e1tica, Universidad de Sevilla, Avd. Reina Mercedes s/n, Sevilla, 41012, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics and Technology of Computers Lab (RTC), ETSI Inform\u00e1tica, Universidad de Sevilla, Avd. Reina Mercedes s/n, Sevilla, 41012, Spain","institution_ids":["https://openalex.org/I79238269"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012722971","display_name":"G. Jim\u00e9nez","orcid":"https://orcid.org/0000-0003-4512-6750"},"institutions":[{"id":"https://openalex.org/I79238269","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24","country_code":"ES","type":"education","lineage":["https://openalex.org/I79238269"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Gabriel Jimenez-Moreno","raw_affiliation_strings":["Robotics and Technology of Computers Lab (RTC), ETSI Inform\u00e1tica, Universidad de Sevilla, Avd. Reina Mercedes s/n, Sevilla, 41012, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Robotics and Technology of Computers Lab (RTC), ETSI Inform\u00e1tica, Universidad de Sevilla, Avd. Reina Mercedes s/n, Sevilla, 41012, Spain","institution_ids":["https://openalex.org/I79238269"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5009965786"],"corresponding_institution_ids":["https://openalex.org/I79238269"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":1.7376,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.82905269,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"53","issue":"24","first_page":"29604","last_page":"29619"},"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":0.9997000098228455,"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":0.9959999918937683,"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/inverse-distance-weighting","display_name":"Inverse distance weighting","score":0.7537604570388794},{"id":"https://openalex.org/keywords/air-quality-index","display_name":"Air quality index","score":0.6291168332099915},{"id":"https://openalex.org/keywords/air-pollution","display_name":"Air pollution","score":0.619179904460907},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6073964238166809},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5559725165367126},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.540554404258728},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5202804207801819},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.45296338200569153},{"id":"https://openalex.org/keywords/pollutant","display_name":"Pollutant","score":0.4238429665565491},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4116235375404358},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.40400606393814087},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37177544832229614},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.31271469593048096},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.2607918977737427},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18906170129776},{"id":"https://openalex.org/keywords/multivariate-interpolation","display_name":"Multivariate interpolation","score":0.16681960225105286}],"concepts":[{"id":"https://openalex.org/C47872207","wikidata":"https://www.wikidata.org/wiki/Q1430701","display_name":"Inverse distance weighting","level":4,"score":0.7537604570388794},{"id":"https://openalex.org/C126314574","wikidata":"https://www.wikidata.org/wiki/Q2364111","display_name":"Air quality index","level":2,"score":0.6291168332099915},{"id":"https://openalex.org/C559116025","wikidata":"https://www.wikidata.org/wiki/Q131123","display_name":"Air pollution","level":2,"score":0.619179904460907},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6073964238166809},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5559725165367126},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.540554404258728},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5202804207801819},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.45296338200569153},{"id":"https://openalex.org/C82685317","wikidata":"https://www.wikidata.org/wiki/Q19829510","display_name":"Pollutant","level":2,"score":0.4238429665565491},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4116235375404358},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.40400606393814087},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37177544832229614},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.31271469593048096},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.2607918977737427},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18906170129776},{"id":"https://openalex.org/C203332170","wikidata":"https://www.wikidata.org/wiki/Q6334079","display_name":"Multivariate interpolation","level":3,"score":0.16681960225105286},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10489-023-05109-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-05109-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-05109-y.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"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":"Applied Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:idus.us.es:11441/163529","is_oa":true,"landing_page_url":"https://idus.us.es/handle//11441/163529","pdf_url":"https://idus.us.es/bitstream/11441/163529/1/A%20systematic%20comparison%20of%20different%20machine%20learning%20models.pdf","source":{"id":"https://openalex.org/S4306400333","display_name":"idUS (Universidad de Sevilla)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79238269","host_organization_name":"Universidad de Sevilla","host_organization_lineage":["https://openalex.org/I79238269"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s10489-023-05109-y","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-023-05109-y","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-023-05109-y.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"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":"Applied Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310967","display_name":"Universidad de Sevilla","ror":"https://ror.org/03yxnpp24"},{"id":"https://openalex.org/F4320335322","display_name":"European Regional Development Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388096911.pdf"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W2003454866","https://openalex.org/W2040316938","https://openalex.org/W2522403126","https://openalex.org/W2902008005","https://openalex.org/W2905944495","https://openalex.org/W2935986185","https://openalex.org/W2947059554","https://openalex.org/W2965521597","https://openalex.org/W2977179014","https://openalex.org/W2981982271","https://openalex.org/W2990955039","https://openalex.org/W2995296280","https://openalex.org/W3000170764","https://openalex.org/W3007246056","https://openalex.org/W3096412676","https://openalex.org/W3096800248","https://openalex.org/W3096834012","https://openalex.org/W3100832220","https://openalex.org/W3108960196","https://openalex.org/W3109735136","https://openalex.org/W3115103108","https://openalex.org/W3117062925","https://openalex.org/W3118566922","https://openalex.org/W3120346671","https://openalex.org/W3120659524","https://openalex.org/W3126881694","https://openalex.org/W3153375240","https://openalex.org/W3168781061","https://openalex.org/W3190073638","https://openalex.org/W3196681873","https://openalex.org/W3196903849","https://openalex.org/W3204245747","https://openalex.org/W4200457728","https://openalex.org/W4220675676","https://openalex.org/W4229562638","https://openalex.org/W4229875153","https://openalex.org/W4239510810","https://openalex.org/W4293775970"],"related_works":["https://openalex.org/W2380877611","https://openalex.org/W2392458002","https://openalex.org/W4221115393","https://openalex.org/W3087863773","https://openalex.org/W3163037427","https://openalex.org/W1585517378","https://openalex.org/W2021907765","https://openalex.org/W2800389260","https://openalex.org/W2498180055","https://openalex.org/W2357092082"],"abstract_inverted_index":{"Abstract":[0],"Air":[1],"pollutants":[2,149],"harm":[3],"human":[4],"health":[5,74],"and":[6,33,46,66,70,115,121,159,177,204,227,239],"the":[7,34,82,91,99,129,138,143,196,206,210,218,223,228,248],"environment.":[8],"Nowadays,":[9],"deploying":[10],"an":[11,51,102,188],"air":[12,23,56,68,95,103,148,190,252],"pollution":[13],"monitoring":[14,105,192],"network":[15,88,133,193],"in":[16,54],"many":[17],"urban":[18,189],"areas":[19],"could":[20],"provide":[21],"real-time":[22],"quality":[24,57,104,191],"assessment.":[25],"However,":[26],"these":[27,110],"networks":[28],"are":[29,234],"usually":[30],"sparsely":[31],"distributed":[32],"sensor":[35],"calibration":[36],"problems":[37],"that":[38],"may":[39],"appear":[40],"over":[41],"time":[42],"lead":[43],"to":[44,60,80,109,127,168,178,236],"missing":[45],"wrong":[47],"measurements.":[48,254],"There":[49],"is":[50],"increasing":[52],"interest":[53],"developing":[55],"modelling":[58],"methods":[59,117,139,238],"minimize":[61],"measurement":[62],"errors,":[63],"predict":[64],"spatial":[65,92,249],"temporal":[67],"quality,":[69],"support":[71],"more":[72],"spatially-resolved":[73],"effect":[75],"analysis.":[76],"This":[77],"research":[78],"aims":[79],"evaluate":[81],"ability":[83,208],"of":[84,94,101,131,137,146,199,209,230,251],"three":[85,212],"feed-forward":[86],"neural":[87,132],"architectures":[89],"for":[90,246],"prediction":[93],"pollutant":[96,253],"concentrations":[97],"using":[98,142],"measures":[100],"network.":[106],"In":[107],"addition":[108],"architectures,":[111],"Support":[112,243],"Vector":[113,244],"Machines":[114,245],"geostatistical":[116,237],"(Inverse":[118],"Distance":[119],"Weighting":[120],"Ordinary":[122],"Kriging)":[123],"were":[124,216],"also":[125],"implemented":[126],"compare":[128,205],"performance":[130],"models.":[134],"The":[135],"evaluation":[136],"was":[140],"performed":[141],"historical":[144],"values":[145],"seven":[147],"(Nitrogen":[150],"monoxide,":[151,157],"Nitrogen":[152],"dioxide,":[153,155],"Sulphur":[154],"Carbon":[156],"Ozone,":[158],"particulate":[160],"matters":[161],"with":[162],"size":[163],"less":[164],"than":[165,242],"or":[166],"equal":[167],"2.5":[169],"$$\\upmu":[170,180],"$$":[171,181],"<mml:math":[172,182],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\">":[173,183],"<mml:mi>\u03bc</mml:mi>":[174,184],"</mml:math>":[175,185],"m":[176],"10":[179],"m)":[186],"from":[187],"located":[194],"at":[195],"metropolitan":[197],"area":[198],"Madrid":[200],"(Spain).":[201],"To":[202],"assess":[203],"predictive":[207],"models,":[211],"estimation":[213],"accuracy":[214],"indicators":[215],"calculated:":[217],"Root":[219],"Mean":[220,224],"Squared":[221],"Error,":[222,226],"Absolute":[225],"coefficient":[229],"determination.":[231],"FFNN-based":[232],"models":[233],"superior":[235],"slightly":[240],"better":[241],"fitting":[247],"correlation":[250],"Graphical":[255],"abstract":[256]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
