{"id":"https://openalex.org/W4403278846","doi":"https://doi.org/10.1109/is61756.2024.10705219","title":"Predicting PM2.5 Air Quality Using Random Forest Regression Enhanced with Polynomial Features","display_name":"Predicting PM2.5 Air Quality Using Random Forest Regression Enhanced with Polynomial Features","publication_year":2024,"publication_date":"2024-08-29","ids":{"openalex":"https://openalex.org/W4403278846","doi":"https://doi.org/10.1109/is61756.2024.10705219"},"language":"en","primary_location":{"id":"doi:10.1109/is61756.2024.10705219","is_oa":false,"landing_page_url":"https://doi.org/10.1109/is61756.2024.10705219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 12th International Conference on Intelligent Systems (IS)","raw_type":"proceedings-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/A5009685311","display_name":"Kunal Goyal","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kunal Goyal","raw_affiliation_strings":["College of Computing Georgia Institute of Technology,Atlanta,Georgia,USA,30332"],"affiliations":[{"raw_affiliation_string":"College of Computing Georgia Institute of Technology,Atlanta,Georgia,USA,30332","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037333525","display_name":"Shreya Goyal","orcid":"https://orcid.org/0000-0002-3629-3701"},"institutions":[{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shreya Goyal","raw_affiliation_strings":["Indiana University-Purdue University Indianapolis,Department of BioHealth Informatics,Indianapolis,Indiana,USA,46202"],"affiliations":[{"raw_affiliation_string":"Indiana University-Purdue University Indianapolis,Department of BioHealth Informatics,Indianapolis,Indiana,USA,46202","institution_ids":["https://openalex.org/I55769427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5009685311"],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":1.5105,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.80839143,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9009000062942505,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7243823409080505},{"id":"https://openalex.org/keywords/polynomial-regression","display_name":"Polynomial regression","score":0.5841599702835083},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5039917826652527},{"id":"https://openalex.org/keywords/air-quality-index","display_name":"Air quality index","score":0.4981517791748047},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4961863160133362},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.4820035994052887},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4775013327598572},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.45420926809310913},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.36372900009155273},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3501160144805908},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33107370138168335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3219265639781952},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2764415740966797},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.17677929997444153},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09962087869644165}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7243823409080505},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.5841599702835083},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5039917826652527},{"id":"https://openalex.org/C126314574","wikidata":"https://www.wikidata.org/wiki/Q2364111","display_name":"Air quality index","level":2,"score":0.4981517791748047},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4961863160133362},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.4820035994052887},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4775013327598572},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.45420926809310913},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.36372900009155273},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3501160144805908},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33107370138168335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3219265639781952},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2764415740966797},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.17677929997444153},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09962087869644165},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/is61756.2024.10705219","is_oa":false,"landing_page_url":"https://doi.org/10.1109/is61756.2024.10705219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 12th International Conference on Intelligent Systems (IS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.47999998927116394,"display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2078706344","https://openalex.org/W2146190867","https://openalex.org/W2150751323","https://openalex.org/W2166604768","https://openalex.org/W2787894218","https://openalex.org/W2799286067","https://openalex.org/W2888532083","https://openalex.org/W2890701797","https://openalex.org/W2908829962","https://openalex.org/W2916789854","https://openalex.org/W2944336783","https://openalex.org/W2945306488","https://openalex.org/W2995296280","https://openalex.org/W3033154016","https://openalex.org/W4223614486","https://openalex.org/W4400762160"],"related_works":["https://openalex.org/W2048488252","https://openalex.org/W4289884158","https://openalex.org/W2940614149","https://openalex.org/W2575826071","https://openalex.org/W4288365262","https://openalex.org/W2390681602","https://openalex.org/W2787485953","https://openalex.org/W3217432596","https://openalex.org/W2379078475","https://openalex.org/W2799339361"],"abstract_inverted_index":{"Fine":[0],"particulate":[1],"matter":[2],"(PM2.5)":[3],"air":[4,99,195,245,291,298],"pollution":[5,292],"is":[6,24,42,54,82,139,168],"a":[7,108,294,303,321],"global":[8,295,305],"public":[9,199,259],"health":[10,69,260],"crisis,":[11],"responsible":[12],"for":[13,26,57,142,194,319],"millions":[14],"of":[15,21,40,79,180,191,237,254,274,290],"premature":[16],"deaths":[17],"annually.":[18],"Accurate":[19],"prediction":[20,78],"PM2.5":[22,41,80,228],"concentrations":[23],"paramount":[25],"timely":[27,77],"alerts,":[28],"effective":[29],"mitigation,":[30],"and":[31,50,65,76,153,164,187,198,222,261,268,323],"informed":[32],"policy":[33,263],"decisions.":[34,264],"Chronic":[35],"exposure":[36],"to":[37,131,146,149,160,208,243,277,285,301],"high":[38],"levels":[39,81],"associated":[43],"with":[44,67,114],"increased":[45],"mortality":[46],"rates":[47],"from":[48,120],"heart":[49],"lung":[51],"diseases.":[52],"This":[53,230],"especially":[55],"concerning":[56],"vulnerable":[58],"populations":[59],"such":[60,216,309],"as":[61,217,310],"children,":[62],"the":[63,92,121,133,173,178,189,205,211,235,251,272,287,311],"elderly,":[64],"individuals":[66],"pre-existing":[68],"conditions.":[70],"To":[71],"address":[72],"this":[73,102,143,275,315],"challenge,":[74],"accurate":[75,255],"essential.":[83],"Traditional":[84],"linear":[85],"models":[86],"often":[87],"fall":[88],"short":[89],"in":[90,257,314],"capturing":[91],"complex":[93,212],"interactions":[94,165,213],"between":[95,166],"multiple":[96],"factors":[97,225],"influencing":[98],"quality.":[100],"Therefore,":[101],"study":[103,231,316],"employs":[104],"Random":[105,136],"Forest":[106,137],"Regression,":[107],"robust":[109],"ensemble":[110],"learning":[111,241],"method,":[112],"enhanced":[113],"polynomial":[115,203],"features":[116],"using":[117,238],"meteorological":[118],"data":[119,152],"U.S.":[122],"Environmental":[123],"Protection":[124],"Agency's":[125],"(EPA)":[126],"Air":[127],"Quality":[128],"System":[129],"(AQS)":[130],"improve":[132],"predictive":[134],"accuracy.":[135],"Regression":[138],"particularly":[140],"suitable":[141],"task":[144],"due":[145],"its":[147],"ability":[148,159],"handle":[150],"high-dimensional":[151],"capture":[154,161,210],"non-linear":[155,162],"relationships.":[156],"The":[157],"model's":[158],"relationships":[163],"predictors":[167],"thoroughly":[169],"evaluated.":[170],"We":[171],"leverage":[172],"extensive":[174],"AQS":[175],"dataset,":[176],"discuss":[177],"intricacies":[179],"feature":[181],"engineering,":[182],"present":[183],"rigorous":[184],"model":[185,206],"validation,":[186,269],"explore":[188],"implications":[190],"our":[192],"findings":[193],"quality":[196,246,299],"management":[197],"health.":[200],"By":[201],"incorporating":[202],"features,":[204],"aims":[207],"better":[209],"among":[214],"variables":[215],"temperature,":[218],"humidity,":[219],"wind":[220],"speed,":[221],"other":[223],"environmental":[224],"that":[226],"influence":[227],"levels.":[229],"not":[232],"only":[233],"highlights":[234],"effectiveness":[236],"advanced":[239],"machine":[240],"techniques":[242],"enhance":[244],"predictions":[247],"but":[248],"also":[249],"underscores":[250],"critical":[252],"role":[253],"forecasting":[256],"protecting":[258],"guiding":[262],"Through":[265],"comprehensive":[266],"analysis":[267],"we":[270],"demonstrate":[271],"potential":[273],"approach":[276],"provide":[278],"more":[279,324],"reliable":[280],"predictions,":[281],"thus":[282],"supporting":[283],"efforts":[284],"mitigate":[286],"adverse":[288],"effects":[289],"on":[293],"scale.":[296],"As":[297],"continues":[300],"be":[302],"pressing":[304],"issue,":[306],"innovative":[307],"approaches":[308],"one":[312],"presented":[313],"are":[317],"essential":[318],"ensuring":[320],"healthier":[322],"sustainable":[325],"future.":[326]},"counts_by_year":[{"year":2025,"cited_by_count":7}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}
