{"id":"https://openalex.org/W2626732771","doi":"https://doi.org/10.1109/tits.2017.2706143","title":"A Functional Data Analysis Approach to Traffic Volume Forecasting","display_name":"A Functional Data Analysis Approach to Traffic Volume Forecasting","publication_year":2017,"publication_date":"2017-06-13","ids":{"openalex":"https://openalex.org/W2626732771","doi":"https://doi.org/10.1109/tits.2017.2706143","mag":"2626732771"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2017.2706143","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2017.2706143","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-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/A5011712347","display_name":"Isaac Michael Wagner-Muns","orcid":"https://orcid.org/0000-0003-0861-363X"},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Isaac Michael Wagner-Muns","raw_affiliation_strings":["Department of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO, USA"],"raw_orcid":"https://orcid.org/0000-0003-0861-363X","affiliations":[{"raw_affiliation_string":"Department of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001732874","display_name":"Ivan G. Guardiola","orcid":"https://orcid.org/0000-0002-7381-5441"},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ivan G. Guardiola","raw_affiliation_strings":["Department of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO, USA"],"raw_orcid":"https://orcid.org/0000-0002-7381-5441","affiliations":[{"raw_affiliation_string":"Department of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108645637","display_name":"V. A. Samaranayke","orcid":null},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"V. A. Samaranayke","raw_affiliation_strings":["Department of Mathematics and Statistics, Missouri University of Science and Technology, Rolla, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, Missouri University of Science and Technology, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033019031","display_name":"Wasim Irshad Kayani","orcid":null},"institutions":[{"id":"https://openalex.org/I20382870","display_name":"Missouri University of Science and Technology","ror":"https://ror.org/00scwqd12","country_code":"US","type":"education","lineage":["https://openalex.org/I20382870"]},{"id":"https://openalex.org/I929597975","display_name":"National University of Sciences and Technology","ror":"https://ror.org/03w2j5y17","country_code":"PK","type":"education","lineage":["https://openalex.org/I929597975"]}],"countries":["PK","US"],"is_corresponding":false,"raw_author_name":"Wasim Irshad Kayani","raw_affiliation_strings":["Department of Civil Engineering, Missouri University of Science and Technology, Rolla, MO, USA","National University of Sciences and Technology, Islamabad, Pakistan","Transportation and Geotechnical Engineering Department, Military College of Engineering, Risalpur Cantonment, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil Engineering, Missouri University of Science and Technology, Rolla, MO, USA","institution_ids":["https://openalex.org/I20382870"]},{"raw_affiliation_string":"National University of Sciences and Technology, Islamabad, Pakistan","institution_ids":["https://openalex.org/I929597975"]},{"raw_affiliation_string":"Transportation and Geotechnical Engineering Department, Military College of Engineering, Risalpur Cantonment, Pakistan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.6027,"has_fulltext":false,"cited_by_count":67,"citation_normalized_percentile":{"value":0.94122911,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"19","issue":"3","first_page":"878","last_page":"888"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9980000257492065,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.6698251962661743},{"id":"https://openalex.org/keywords/functional-data-analysis","display_name":"Functional data analysis","score":0.6047565937042236},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.6020108461380005},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5841208100318909},{"id":"https://openalex.org/keywords/traffic-volume","display_name":"Traffic volume","score":0.5784488916397095},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5567712187767029},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.5232681035995483},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5190849304199219},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5091974139213562},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4775187075138092},{"id":"https://openalex.org/keywords/functional-principal-component-analysis","display_name":"Functional principal component analysis","score":0.4769367575645447},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.434389591217041},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4294761121273041},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.29068130254745483},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.272258996963501},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2362423539161682},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17804691195487976},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17363882064819336},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15014776587486267},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.11972165107727051}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.6698251962661743},{"id":"https://openalex.org/C51820054","wikidata":"https://www.wikidata.org/wiki/Q5508814","display_name":"Functional data analysis","level":2,"score":0.6047565937042236},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.6020108461380005},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5841208100318909},{"id":"https://openalex.org/C168443057","wikidata":"https://www.wikidata.org/wiki/Q7001223","display_name":"Traffic volume","level":2,"score":0.5784488916397095},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5567712187767029},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.5232681035995483},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5190849304199219},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5091974139213562},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4775187075138092},{"id":"https://openalex.org/C71176878","wikidata":"https://www.wikidata.org/wiki/Q17014987","display_name":"Functional principal component analysis","level":3,"score":0.4769367575645447},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.434389591217041},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4294761121273041},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.29068130254745483},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.272258996963501},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2362423539161682},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17804691195487976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17363882064819336},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15014776587486267},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.11972165107727051},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2017.2706143","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2017.2706143","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309636","display_name":"University of Minnesota","ror":"https://ror.org/03grvy078"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W20499850","https://openalex.org/W163215356","https://openalex.org/W595743366","https://openalex.org/W618865624","https://openalex.org/W628208226","https://openalex.org/W649348608","https://openalex.org/W1522676482","https://openalex.org/W1576898078","https://openalex.org/W1603304768","https://openalex.org/W1907566654","https://openalex.org/W1964965419","https://openalex.org/W1982978808","https://openalex.org/W1986925696","https://openalex.org/W1996596461","https://openalex.org/W2004073866","https://openalex.org/W2024558842","https://openalex.org/W2025379728","https://openalex.org/W2036785686","https://openalex.org/W2037416370","https://openalex.org/W2040297119","https://openalex.org/W2046835809","https://openalex.org/W2049500727","https://openalex.org/W2050096169","https://openalex.org/W2065139931","https://openalex.org/W2077212262","https://openalex.org/W2078825359","https://openalex.org/W2083438019","https://openalex.org/W2108196201","https://openalex.org/W2116175937","https://openalex.org/W2125817951","https://openalex.org/W2131087111","https://openalex.org/W2135009431","https://openalex.org/W2141589598","https://openalex.org/W2156423229","https://openalex.org/W2161731530","https://openalex.org/W2166988467","https://openalex.org/W2177262641","https://openalex.org/W2514294276","https://openalex.org/W2544396242","https://openalex.org/W2554404266","https://openalex.org/W2811189031","https://openalex.org/W3021971632","https://openalex.org/W3101764587","https://openalex.org/W4205462863","https://openalex.org/W4240810135","https://openalex.org/W6618136148","https://openalex.org/W6631251400","https://openalex.org/W6659849045","https://openalex.org/W6680724847"],"related_works":["https://openalex.org/W2299080873","https://openalex.org/W273216563","https://openalex.org/W2963184067","https://openalex.org/W2605967135","https://openalex.org/W2056592727","https://openalex.org/W1925427981","https://openalex.org/W2340639288","https://openalex.org/W3124114881","https://openalex.org/W3169146846","https://openalex.org/W2085579733"],"abstract_inverted_index":{"Traffic":[0],"volume":[1,57,75],"forecasts":[2,86],"are":[3,87],"used":[4],"by":[5],"many":[6],"transportation":[7],"analysis":[8,51,113],"and":[9,15,102],"management":[10],"systems":[11],"to":[12,17,38,52,89],"better":[13],"characterize":[14],"react":[16],"fluctuating":[18],"traffic":[19,56,74],"patterns.":[20],"Most":[21],"current":[22],"forecasting":[23],"methods":[24,97],"do":[25],"not":[26],"take":[27],"advantage":[28],"of":[29,34,67,70,118,122],"the":[30,35,84,110,115,119,123],"underlying":[31],"functional":[32,48,85,111],"characteristics":[33],"time":[36,76],"series":[37],"make":[39],"predictions.":[40],"This":[41],"paper":[42],"presents":[43],"a":[44,64],"methodology":[45,60],"that":[46],"uses":[47],"principal":[49],"components":[50],"create":[53],"high-quality":[54],"online":[55],"forecasts.":[58],"The":[59],"is":[61],"validated":[62],"with":[63,79],"data":[65,112,124],"set":[66],"1755":[68],"days":[69],"15":[71],"min":[72],"aggregated":[73],"series.":[77],"Compared":[78],"365":[80],"randomly":[81],"selected":[82],"days,":[83],"found":[88],"outperform":[90],"traditional":[91],"seasonal":[92],"autoregressive":[93],"integrated":[94],"moving":[95],"average-based":[96],"in":[98],"both":[99],"count":[100],"deviation":[101],"root":[103],"mean":[104],"squared":[105],"error.":[106],"In":[107],"addition,":[108],"through":[109],"approach":[114],"full":[116],"exploitation":[117],"continuous":[120],"nature":[121],"can":[125],"be":[126],"achieved.":[127]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":3}],"updated_date":"2026-07-17T09:13:05.818461","created_date":"2025-10-10T00:00:00"}