{"id":"https://openalex.org/W2011218133","doi":"https://doi.org/10.1109/icnc.2014.6975827","title":"A comparative study on multi-regression analysis and BP neural network of PM2.5 index","display_name":"A comparative study on multi-regression analysis and BP neural network of PM2.5 index","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W2011218133","doi":"https://doi.org/10.1109/icnc.2014.6975827","mag":"2011218133"},"language":"en","primary_location":{"id":"doi:10.1109/icnc.2014.6975827","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2014.6975827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 10th International Conference on Natural Computation (ICNC)","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/A5100675121","display_name":"Yuan Chen","orcid":"https://orcid.org/0000-0001-8887-384X"},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuan Chen","raw_affiliation_strings":["College of Mathematics and Computer Seience, Wuhan Textile University, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Seience, Wuhan Textile University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I4210119942"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100586459","display_name":"Hui Qin","orcid":"https://orcid.org/0000-0002-8805-0015"},"institutions":[{"id":"https://openalex.org/I184681353","display_name":"Anhui University of Science and Technology","ror":"https://ror.org/00q9atg80","country_code":"CN","type":"education","lineage":["https://openalex.org/I184681353"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Qin","raw_affiliation_strings":["College of Science, Anhui University of Science and Technology, Huainan, Anhui, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Science, Anhui University of Science and Technology, Huainan, Anhui, China","institution_ids":["https://openalex.org/I184681353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081442336","display_name":"Zhigang Zhou","orcid":"https://orcid.org/0000-0003-0591-2319"},"institutions":[{"id":"https://openalex.org/I4210119942","display_name":"Wuhan Textile University","ror":"https://ror.org/02jgsf398","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210119942"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ZhiGang Zhou","raw_affiliation_strings":["College of Mathematics and Computer Science, Wuhan Textile University, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer Science, Wuhan Textile University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I4210119942"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100675121"],"corresponding_institution_ids":["https://openalex.org/I4210119942"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.10418261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"155","last_page":"159"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing 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/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing 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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9690999984741211,"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/T14474","display_name":"Industrial Technology and Control Systems","score":0.9435999989509583,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.7654070854187012},{"id":"https://openalex.org/keywords/yesterday","display_name":"Yesterday","score":0.5890320539474487},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.5661300420761108},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5125939249992371},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.49543654918670654},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.49006402492523193},{"id":"https://openalex.org/keywords/air-pollution-index","display_name":"Air Pollution Index","score":0.4687533378601074},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.4479198753833771},{"id":"https://openalex.org/keywords/precipitation","display_name":"Precipitation","score":0.439251184463501},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4206005334854126},{"id":"https://openalex.org/keywords/dew-point","display_name":"Dew point","score":0.41522324085235596},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41225653886795044},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.40418657660484314},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3937719762325287},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.267109751701355},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23091533780097961},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23012518882751465},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2186734676361084},{"id":"https://openalex.org/keywords/air-quality-index","display_name":"Air quality index","score":0.18597334623336792}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7654070854187012},{"id":"https://openalex.org/C2777840570","wikidata":"https://www.wikidata.org/wiki/Q1187312","display_name":"Yesterday","level":2,"score":0.5890320539474487},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.5661300420761108},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5125939249992371},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.49543654918670654},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.49006402492523193},{"id":"https://openalex.org/C2777570903","wikidata":"https://www.wikidata.org/wiki/Q4698151","display_name":"Air Pollution Index","level":3,"score":0.4687533378601074},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.4479198753833771},{"id":"https://openalex.org/C107054158","wikidata":"https://www.wikidata.org/wiki/Q25257","display_name":"Precipitation","level":2,"score":0.439251184463501},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4206005334854126},{"id":"https://openalex.org/C82210777","wikidata":"https://www.wikidata.org/wiki/Q178828","display_name":"Dew point","level":2,"score":0.41522324085235596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41225653886795044},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.40418657660484314},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3937719762325287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.267109751701355},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23091533780097961},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23012518882751465},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2186734676361084},{"id":"https://openalex.org/C126314574","wikidata":"https://www.wikidata.org/wiki/Q2364111","display_name":"Air quality index","level":2,"score":0.18597334623336792},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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/icnc.2014.6975827","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2014.6975827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 10th International Conference on Natural Computation (ICNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W16709935","https://openalex.org/W1575772124","https://openalex.org/W2118756059","https://openalex.org/W2355660776","https://openalex.org/W2361361730","https://openalex.org/W2364446892","https://openalex.org/W2392133284","https://openalex.org/W7008420565","https://openalex.org/W7062127998"],"related_works":["https://openalex.org/W2467605997","https://openalex.org/W2277613585","https://openalex.org/W2039249127","https://openalex.org/W4239479552","https://openalex.org/W2040195038","https://openalex.org/W2037292558","https://openalex.org/W2605528207","https://openalex.org/W4238091389","https://openalex.org/W2078182361","https://openalex.org/W3175678658"],"abstract_inverted_index":{"The":[0,12,42,85,110],"air":[1,52,70],"pollution":[2,53,71],"PM2.5":[3,40,54,72],"index":[4,19,55,73],"is":[5,118],"affected":[6],"by":[7],"a":[8],"variety":[9],"of":[10,20,23,47,56,119,133],"factors.":[11],"research":[13,135],"shows":[14,88],"that":[15,89],"the":[16,34,45,69,101,105],"PM":[17],"2.5":[18],"yesterday,":[21,24],"precipitation":[22,29],"average":[25,27],"temperature,":[26],"humidity,":[28],"and":[30,51,81,123,136],"wind":[31],"velocity":[32],"are":[33],"main":[35],"factors":[36,107],"which":[37,127],"can":[38,128],"affect":[39],"index.":[41],"paper":[43],"utilizes":[44],"data":[46],"surface":[48],"meteorological":[49],"observation":[50],"Wuhan":[57],"City":[58],"from":[59],"November":[60],"1,":[61],"2013":[62],"to":[63,77,91,140],"January":[64],"31,":[65],"2014.":[66],"We":[67],"construct":[68],"forecasting":[74],"model":[75,99,112],"according":[76],"multiple":[78],"regression":[79,92],"analysis":[80],"BP":[82,95,115],"neural":[83,96,116],"network.":[84],"empirical":[86],"study":[87],"compared":[90],"prediction":[93,98,106,125,134],"model,":[94],"network":[97,117],"obtains":[100],"nonlinear":[102],"relation":[103],"among":[104],"after":[108],"training.":[109],"predictive":[111,121],"based":[113],"on":[114],"higher":[120],"precision":[122],"better":[124],"effect":[126],"be":[129],"used":[130],"in":[131],"kinds":[132],"has":[137],"good":[138],"value":[139],"popularize.":[141]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2025-10-10T00:00:00"}
