{"id":"https://openalex.org/W2219956463","doi":"https://doi.org/10.1109/soli.2015.7367614","title":"A hybrid model for short-term air pollutant concentration forecasting","display_name":"A hybrid model for short-term air pollutant concentration forecasting","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2219956463","doi":"https://doi.org/10.1109/soli.2015.7367614","mag":"2219956463"},"language":"en","primary_location":{"id":"doi:10.1109/soli.2015.7367614","is_oa":false,"landing_page_url":"https://doi.org/10.1109/soli.2015.7367614","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Service Operations And Logistics, And Informatics (SOLI)","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/A5100327539","display_name":"Xin Zhang","orcid":"https://orcid.org/0000-0002-9291-0671"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Zhang","raw_affiliation_strings":["IBM Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, Beijing, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066470220","display_name":"Xiaoguang Rui","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoguang Rui","raw_affiliation_strings":["IBM Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, Beijing, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103662131","display_name":"Xi Xia","orcid":"https://orcid.org/0000-0002-3396-9243"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Xia","raw_affiliation_strings":["IBM Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, Beijing, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060495018","display_name":"Xinxin Bai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinxin Bai","raw_affiliation_strings":["IBM Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, Beijing, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110196535","display_name":"Wenjun Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjun Yin","raw_affiliation_strings":["IBM Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, Beijing, China","institution_ids":["https://openalex.org/I4210126794"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012002316","display_name":"Jin Dong","orcid":"https://orcid.org/0000-0002-5753-1588"},"institutions":[{"id":"https://openalex.org/I4210126794","display_name":"IBM Research (China)","ror":"https://ror.org/02yg1pf55","country_code":"CN","type":"company","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115","https://openalex.org/I4210126794"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Dong","raw_affiliation_strings":["IBM Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"IBM Research, Beijing, China","institution_ids":["https://openalex.org/I4210126794"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100327539"],"corresponding_institution_ids":["https://openalex.org/I4210126794"],"apc_list":null,"apc_paid":null,"fwci":0.2271,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.61595683,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"171","last_page":"175"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9968000054359436,"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":0.9968000054359436,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11821","display_name":"Odor and Emission Control Technologies","score":0.9760000109672546,"subfield":{"id":"https://openalex.org/subfields/1508","display_name":"Process Chemistry and Technology"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/nonlinear-autoregressive-exogenous-model","display_name":"Nonlinear autoregressive exogenous model","score":0.9645813703536987},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.8368841409683228},{"id":"https://openalex.org/keywords/autoregressive\u2013moving-average-model","display_name":"Autoregressive\u2013moving-average model","score":0.6488832235336304},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6309068202972412},{"id":"https://openalex.org/keywords/pollutant","display_name":"Pollutant","score":0.6219477653503418},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5466939210891724},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5417528748512268},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5385720729827881},{"id":"https://openalex.org/keywords/air-pollutants","display_name":"Air pollutants","score":0.44874095916748047},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.39873793721199036},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.3366042375564575},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.32588648796081543},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.28348028659820557},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20460641384124756},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16751450300216675},{"id":"https://openalex.org/keywords/air-pollution","display_name":"Air pollution","score":0.15866830945014954},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0652511715888977}],"concepts":[{"id":"https://openalex.org/C42536954","wikidata":"https://www.wikidata.org/wiki/Q7049462","display_name":"Nonlinear autoregressive exogenous model","level":3,"score":0.9645813703536987},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.8368841409683228},{"id":"https://openalex.org/C74883015","wikidata":"https://www.wikidata.org/wiki/Q290467","display_name":"Autoregressive\u2013moving-average model","level":3,"score":0.6488832235336304},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6309068202972412},{"id":"https://openalex.org/C82685317","wikidata":"https://www.wikidata.org/wiki/Q19829510","display_name":"Pollutant","level":2,"score":0.6219477653503418},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5466939210891724},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5417528748512268},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5385720729827881},{"id":"https://openalex.org/C2987853052","wikidata":"https://www.wikidata.org/wiki/Q131123","display_name":"Air pollutants","level":3,"score":0.44874095916748047},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.39873793721199036},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.3366042375564575},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.32588648796081543},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.28348028659820557},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20460641384124756},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16751450300216675},{"id":"https://openalex.org/C559116025","wikidata":"https://www.wikidata.org/wiki/Q131123","display_name":"Air pollution","level":2,"score":0.15866830945014954},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0652511715888977},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"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/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/soli.2015.7367614","is_oa":false,"landing_page_url":"https://doi.org/10.1109/soli.2015.7367614","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Service Operations And Logistics, And Informatics (SOLI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310207","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1982115778","https://openalex.org/W2072809394","https://openalex.org/W2101559758","https://openalex.org/W2106595237","https://openalex.org/W2110085889","https://openalex.org/W2110312652","https://openalex.org/W2117457276","https://openalex.org/W2125733767","https://openalex.org/W2133638105","https://openalex.org/W2136767227","https://openalex.org/W2165010888","https://openalex.org/W2268207689","https://openalex.org/W2532706961","https://openalex.org/W6680600804"],"related_works":["https://openalex.org/W2606910468","https://openalex.org/W3116827148","https://openalex.org/W3120843198","https://openalex.org/W2799656149","https://openalex.org/W2154965898","https://openalex.org/W2036704594","https://openalex.org/W4226315710","https://openalex.org/W3083782034","https://openalex.org/W4287185323","https://openalex.org/W2995801509"],"abstract_inverted_index":{"The":[0,33,59,82],"paper":[1],"focuses":[2],"on":[3],"short-term":[4],"forecasting":[5],"of":[6,18,42,61,69],"air":[7],"pollutants":[8,98],"including":[9],"SO2,":[10],"NO2,":[11],"O3":[12],"and":[13,26,44,75,87,90],"PM2.5.":[14],"A":[15],"hybrid":[16,63],"model":[17,49,64,83],"nonlinear":[19,43,86],"autoregressive":[20,27],"with":[21],"exogenous":[22,80],"input":[23],"(NARX)":[24],"network":[25,35],"moving":[28],"average":[29],"(ARMA)":[30],"is":[31,36,50,65],"applied.":[32],"NARX":[34],"used":[37],"to":[38,52],"solve":[39],"the":[40,47,54,62,85,97],"problem":[41,89],"multidimensional":[45,88],"while":[46],"ARMA":[48],"aimed":[51],"improve":[53],"flexibility":[55],"for":[56,95],"different":[57],"pollutants.":[58],"performance":[60],"evaluated":[66],"by":[67],"data":[68],"pollutant":[70],"concentration":[71],"as":[72,79],"basic":[73],"input,":[74],"observed/forecast":[76],"weather":[77],"condition":[78],"input.":[81],"overcomes":[84],"shows":[91],"promising":[92],"overall":[93],"results":[94],"all":[96],"over":[99],"traditional":[100],"method.":[101]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}