{"id":"https://openalex.org/W3091603436","doi":"https://doi.org/10.1109/acit49673.2020.9208968","title":"High-Accuracy Particulate Matter Prediction Model Based on Artificial Neural Network","display_name":"High-Accuracy Particulate Matter Prediction Model Based on Artificial Neural Network","publication_year":2020,"publication_date":"2020-09-01","ids":{"openalex":"https://openalex.org/W3091603436","doi":"https://doi.org/10.1109/acit49673.2020.9208968","mag":"3091603436"},"language":"en","primary_location":{"id":"doi:10.1109/acit49673.2020.9208968","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit49673.2020.9208968","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 10th International Conference on Advanced Computer Information Technologies (ACIT)","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/A5017004453","display_name":"Jelena Mi\u0161i\u0107","orcid":"https://orcid.org/0000-0002-1251-3730"},"institutions":[{"id":"https://openalex.org/I152518017","display_name":"University of Nis","ror":"https://ror.org/00965bg92","country_code":"RS","type":"education","lineage":["https://openalex.org/I152518017"]}],"countries":["RS"],"is_corresponding":true,"raw_author_name":"Jelena Misic","raw_affiliation_strings":["Department of Telecommunications, Faculty of Electronic Engineering, Nis, Serbia"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunications, Faculty of Electronic Engineering, Nis, Serbia","institution_ids":["https://openalex.org/I152518017"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101927218","display_name":"Vera Markovi\u0107","orcid":"https://orcid.org/0009-0007-5187-1382"},"institutions":[{"id":"https://openalex.org/I152518017","display_name":"University of Nis","ror":"https://ror.org/00965bg92","country_code":"RS","type":"education","lineage":["https://openalex.org/I152518017"]}],"countries":["RS"],"is_corresponding":false,"raw_author_name":"Vera Markovic","raw_affiliation_strings":["Department of Telecommunications, Faculty of Electronic Engineering, Nis, Serbia"],"affiliations":[{"raw_affiliation_string":"Department of Telecommunications, Faculty of Electronic Engineering, Nis, Serbia","institution_ids":["https://openalex.org/I152518017"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017004453"],"corresponding_institution_ids":["https://openalex.org/I152518017"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08969744,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"63","issue":null,"first_page":"404","last_page":"407"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":1.0,"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":1.0,"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":0.9995999932289124,"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":0.9986000061035156,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.7810962200164795},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.7259930372238159},{"id":"https://openalex.org/keywords/particulates","display_name":"Particulates","score":0.6897123456001282},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5499184727668762},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4707917273044586},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.435865193605423},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.43405386805534363},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43047747015953064},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4154536724090576},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3715894818305969},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.32814857363700867}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7810962200164795},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.7259930372238159},{"id":"https://openalex.org/C24245907","wikidata":"https://www.wikidata.org/wiki/Q498957","display_name":"Particulates","level":2,"score":0.6897123456001282},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5499184727668762},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4707917273044586},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.435865193605423},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.43405386805534363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43047747015953064},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4154536724090576},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3715894818305969},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.32814857363700867},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acit49673.2020.9208968","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acit49673.2020.9208968","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 10th International Conference on Advanced Computer Information Technologies (ACIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1975435017","https://openalex.org/W2003366520","https://openalex.org/W2011218133","https://openalex.org/W2029746172","https://openalex.org/W2031253610","https://openalex.org/W2073133301","https://openalex.org/W2117457276","https://openalex.org/W2159144360","https://openalex.org/W2161778665","https://openalex.org/W2480172761","https://openalex.org/W2778213743","https://openalex.org/W2792107246","https://openalex.org/W2916789854","https://openalex.org/W6683497351"],"related_works":["https://openalex.org/W626601394","https://openalex.org/W2494533905","https://openalex.org/W2941015101","https://openalex.org/W2371666510","https://openalex.org/W3158157485","https://openalex.org/W2789124470","https://openalex.org/W3000407446","https://openalex.org/W2116531472","https://openalex.org/W2103550798","https://openalex.org/W1926317180"],"abstract_inverted_index":{"This":[0],"paper":[1,71],"presents":[2],"a":[3,75,127],"low-cost":[4],"high-accuracy":[5],"method":[6,67],"for":[7],"the":[8,11,37,56,88,108,119,132],"prediction":[9,58,97,122,134],"of":[10,60,131],"air":[12],"pollutant":[13,20],"Particulate":[14],"Matter":[15],"2.5":[16],"(PM2.5).":[17],"The":[18,63,82,96],"PM2.5":[19,39,46,57,83],"is":[21,59,72,85,124],"very":[22],"harmful":[23],"to":[24,94],"humans,":[25],"animals,":[26],"and":[27,29,45,65,113],"vegetation,":[28],"its":[30],"index":[31],"depends":[32],"on":[33,74],"many":[34],"factors.":[35],"As":[36],"existing":[38],"monitoring":[40],"methods":[41],"are":[42,48,92],"mostly":[43],"expensive,":[44],"values":[47],"usually":[49],"not":[50],"measured":[51],"at":[52,102,106],"every":[53],"meteorological":[54,89],"station,":[55],"great":[61,128],"importance.":[62],"cost-effective":[64],"efficient":[66],"proposed":[68,133],"in":[69],"this":[70],"based":[73],"Multilayer":[76],"Perceptron":[77],"Artificial":[78],"Neural":[79],"Network":[80],"(MLP-ANN).":[81],"level":[84],"predicted":[86],"using":[87],"factors":[90],"that":[91],"easy":[93],"measure.":[95],"accuracy":[98,123],"has":[99],"been":[100],"tested":[101],"two":[103],"locations:":[104],"one":[105],"which":[107],"training":[109],"data":[110],"were":[111],"collected,":[112],"another":[114],"250":[115],"km":[116],"away":[117],"from":[118],"first.":[120],"Excellent":[121],"achieved,":[125],"showing":[126],"practical":[129],"significance":[130],"method.":[135]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
