{"id":"https://openalex.org/W2043798355","doi":"https://doi.org/10.1145/2536146.2536176","title":"Assessment of ARIMA-based prediction techniques for road-traffic volume","display_name":"Assessment of ARIMA-based prediction techniques for road-traffic volume","publication_year":2013,"publication_date":"2013-10-28","ids":{"openalex":"https://openalex.org/W2043798355","doi":"https://doi.org/10.1145/2536146.2536176","mag":"2043798355"},"language":"en","primary_location":{"id":"doi:10.1145/2536146.2536176","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2536146.2536176","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifth International Conference on Management of Emergent Digital EcoSystems","raw_type":"proceedings-article"},"type":"conference-paper","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/A5081658689","display_name":"Vinay B. Gavirangaswamy","orcid":null},"institutions":[{"id":"https://openalex.org/I141649380","display_name":"Western Michigan University","ror":"https://ror.org/04j198w64","country_code":"US","type":"education","lineage":["https://openalex.org/I141649380"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vinay B. Gavirangaswamy","raw_affiliation_strings":["Western Michigan University, Kalamazoo, MI","Western Michigan University; Kalamazoo; MI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western Michigan University, Kalamazoo, MI","institution_ids":["https://openalex.org/I141649380"]},{"raw_affiliation_string":"Western Michigan University; Kalamazoo; MI","institution_ids":["https://openalex.org/I141649380"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101803496","display_name":"Gagan Raj Gupta","orcid":"https://orcid.org/0000-0002-8568-2949"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gagan Gupta","raw_affiliation_strings":["Kalamazoo Area, Mathematics & Science Ctr., Kalamazoo, MI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kalamazoo Area, Mathematics & Science Ctr., Kalamazoo, MI","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028134056","display_name":"Ajay Gupta","orcid":"https://orcid.org/0000-0001-7881-4010"},"institutions":[{"id":"https://openalex.org/I141649380","display_name":"Western Michigan University","ror":"https://ror.org/04j198w64","country_code":"US","type":"education","lineage":["https://openalex.org/I141649380"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ajay Gupta","raw_affiliation_strings":["Western Michigan University, Kalamazoo, MI","Western Michigan University; Kalamazoo; MI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western Michigan University, Kalamazoo, MI","institution_ids":["https://openalex.org/I141649380"]},{"raw_affiliation_string":"Western Michigan University; Kalamazoo; MI","institution_ids":["https://openalex.org/I141649380"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016702627","display_name":"Rajeev Agrawal","orcid":"https://orcid.org/0000-0002-5415-5230"},"institutions":[{"id":"https://openalex.org/I35777872","display_name":"North Carolina Agricultural and Technical State University","ror":"https://ror.org/02aze4h65","country_code":"US","type":"education","lineage":["https://openalex.org/I35777872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rajeev Agrawal","raw_affiliation_strings":["State Univ., Greensboro, NC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Univ., Greensboro, NC","institution_ids":["https://openalex.org/I35777872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"246","last_page":"251"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10698","display_name":"Transportation Planning and Optimization","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9962999820709229,"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/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.9500417709350586},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.6193627119064331},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5950406193733215},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.5778115391731262},{"id":"https://openalex.org/keywords/traffic-volume","display_name":"Traffic volume","score":0.549299955368042},{"id":"https://openalex.org/keywords/autoregressive-conditional-heteroskedasticity","display_name":"Autoregressive conditional heteroskedasticity","score":0.5404629707336426},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5139715075492859},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.5102047920227051},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4914819002151489},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.43529215455055237},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3878452181816101},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.3728516697883606},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.32907962799072266},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2481023371219635},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18337732553482056},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14002355933189392},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1179165244102478},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.11394244432449341},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.10121774673461914}],"concepts":[{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.9500417709350586},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.6193627119064331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5950406193733215},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.5778115391731262},{"id":"https://openalex.org/C168443057","wikidata":"https://www.wikidata.org/wiki/Q7001223","display_name":"Traffic volume","level":2,"score":0.549299955368042},{"id":"https://openalex.org/C23922673","wikidata":"https://www.wikidata.org/wiki/Q180752","display_name":"Autoregressive conditional heteroskedasticity","level":3,"score":0.5404629707336426},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5139715075492859},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.5102047920227051},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4914819002151489},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.43529215455055237},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3878452181816101},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.3728516697883606},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.32907962799072266},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2481023371219635},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18337732553482056},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14002355933189392},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1179165244102478},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.11394244432449341},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.10121774673461914},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"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:10.1145/2536146.2536176","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2536146.2536176","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifth International Conference on Management of Emergent Digital EcoSystems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W561142666","https://openalex.org/W1973943669","https://openalex.org/W1999996900","https://openalex.org/W2005248249","https://openalex.org/W2024760831","https://openalex.org/W2027392238","https://openalex.org/W2039417141","https://openalex.org/W2058083416","https://openalex.org/W2086980903","https://openalex.org/W2105107431","https://openalex.org/W2111991989","https://openalex.org/W2150010190","https://openalex.org/W2798058877"],"related_works":["https://openalex.org/W2390482703","https://openalex.org/W757926711","https://openalex.org/W3141771572","https://openalex.org/W2143853213","https://openalex.org/W1509410003","https://openalex.org/W2791931166","https://openalex.org/W2048598777","https://openalex.org/W2376376438","https://openalex.org/W2112329016","https://openalex.org/W2317459805"],"abstract_inverted_index":{"Studies":[0],"related":[1],"to":[2,38],"public":[3,9],"transportation":[4],"systems":[5],"help":[6],"the":[7,42,51,73,81],"commuting":[8],"by":[10],"increasing":[11],"road":[12,119],"safety":[13],"and":[14,26,77,97,115,127,150,154],"circulation.":[15],"These":[16],"result":[17],"in":[18,160],"optimized":[19],"traffic":[20,83,88,120,138,152],"flow,":[21],"shorter":[22],"origin-destination":[23],"travel":[24],"time":[25],"reduced":[27],"incident":[28],"rate.":[29],"Vehicular":[30],"Ad-Hoc":[31],"Network":[32],"uses":[33],"a":[34],"number":[35],"of":[36,61,75,80,95,101,148],"sensors":[37],"gather":[39],"data":[40,89],"on":[41,72],"road.":[43],"Intelligent":[44],"Transportation":[45],"Systems":[46],"(ITS)":[47],"draw":[48],"inference":[49],"from":[50],"gathered":[52],"data.":[53],"In":[54],"this":[55],"paper":[56],"we":[57],"discuss":[58],"our":[59],"experience":[60],"using":[62],"Auto":[63],"Regressive":[64],"Integrated":[65],"Moving":[66],"Average":[67],"(ARIMA)":[68],"based":[69],"techniques":[70],"emphasizing":[71],"integration":[74],"short-range":[76],"long-range":[78],"dependencies":[79],"historical":[82,137,151],"volume.":[84],"We":[85,110,140],"also":[86],"analyze":[87],"for":[90,107,129,157],"patterns":[91],"across":[92,135,145],"different":[93,136,146],"types":[94,147],"roads":[96,149],"derive":[98],"computational":[99],"complexity":[100],"ARIMA.":[102],"Finally,":[103],"improvements":[104],"are":[105],"identified":[106],"better":[108,124],"prediction.":[109,121],"empirically":[111],"show":[112],"that":[113],"SARIMA":[114,128],"ARIMA-GARCH":[116,122],"exhibit":[117],"similar":[118],"is":[123],"than":[125],"ARIMA":[126],"prediction,":[130],"with":[131],"stable":[132],"model":[133,143],"order":[134],"volumes.":[139],"further":[141],"analyzes":[142],"orders":[144],"volume;":[153],"its":[155],"implications":[156],"practical":[158],"applicability":[159],"ITS.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}