{"id":"https://openalex.org/W4210431740","doi":"https://doi.org/10.1109/access.2022.3149059","title":"Entropy-Based Traffic Flow Labeling for CNN-Based Traffic Congestion Prediction From Meta-Parameters","display_name":"Entropy-Based Traffic Flow Labeling for CNN-Based Traffic Congestion Prediction From Meta-Parameters","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4210431740","doi":"https://doi.org/10.1109/access.2022.3149059"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3149059","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3149059","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09703355.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09703355.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086179903","display_name":"Mouna Zouari Mehdi","orcid":"https://orcid.org/0000-0002-7061-3158"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Mouna Zouari Mehdi","raw_affiliation_strings":["CEM Laboratory, National Engineering School of Sfax, Sfax University, Sfax, Tunisia"],"raw_orcid":"https://orcid.org/0000-0002-7061-3158","affiliations":[{"raw_affiliation_string":"CEM Laboratory, National Engineering School of Sfax, Sfax University, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021363213","display_name":"Habib M. Kammoun","orcid":"https://orcid.org/0000-0002-3330-8242"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Habib M. Kammoun","raw_affiliation_strings":["REsearch Groups in Intelligent Machines (ReGIM-Laboratory), National Engineering School of Sfax, Sfax University, Sfax, Tunisia"],"raw_orcid":"https://orcid.org/0000-0002-3330-8242","affiliations":[{"raw_affiliation_string":"REsearch Groups in Intelligent Machines (ReGIM-Laboratory), National Engineering School of Sfax, Sfax University, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057860559","display_name":"Norhene Gargouri Ben Ayed","orcid":"https://orcid.org/0000-0003-1613-2115"},"institutions":[{"id":"https://openalex.org/I4210119561","display_name":"Digital Research Centre of Sfax","ror":"https://ror.org/02s48dm85","country_code":"TN","type":"facility","lineage":["https://openalex.org/I4210119561"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Norhene Gargouri Benayed","raw_affiliation_strings":["Research Digital Center of Sfax, Technopole of Sfax, Sfax, Tunisia"],"raw_orcid":"https://orcid.org/0000-0003-1613-2115","affiliations":[{"raw_affiliation_string":"Research Digital Center of Sfax, Technopole of Sfax, Sfax, Tunisia","institution_ids":["https://openalex.org/I4210119561"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008162054","display_name":"Dorra Sellami","orcid":"https://orcid.org/0000-0002-7235-6984"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Dorra Sellami","raw_affiliation_strings":["CEM Laboratory, National Engineering School of Sfax, Sfax University, Sfax, Tunisia"],"raw_orcid":"https://orcid.org/0000-0002-7235-6984","affiliations":[{"raw_affiliation_string":"CEM Laboratory, National Engineering School of Sfax, Sfax University, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068336021","display_name":"Alima Damak Masmoudi","orcid":null},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Alima Damak Masmoudi","raw_affiliation_strings":["CEM Laboratory, National Engineering School of Sfax, Sfax University, Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CEM Laboratory, National Engineering School of Sfax, Sfax University, Sfax, Tunisia","institution_ids":["https://openalex.org/I142899784"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.1228,"has_fulltext":true,"cited_by_count":49,"citation_normalized_percentile":{"value":0.95066185,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"10","issue":null,"first_page":"16123","last_page":"16133"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T12095","display_name":"Vehicle emissions and performance","score":0.9944999814033508,"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"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.9919000267982483,"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/computer-science","display_name":"Computer science","score":0.7662976980209351},{"id":"https://openalex.org/keywords/traffic-congestion-reconstruction-with-kerners-three-phase-theory","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","score":0.6615104079246521},{"id":"https://openalex.org/keywords/traffic-congestion","display_name":"Traffic congestion","score":0.6521226167678833},{"id":"https://openalex.org/keywords/randomness","display_name":"Randomness","score":0.5859001278877258},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.466656893491745},{"id":"https://openalex.org/keywords/floating-car-data","display_name":"Floating car data","score":0.4555538594722748},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43786129355430603},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.4253098666667938},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40903428196907043},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3587588369846344},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28380119800567627},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.23903679847717285},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1546666920185089},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.15268856287002563},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09578371047973633},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09271568059921265}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7662976980209351},{"id":"https://openalex.org/C25492975","wikidata":"https://www.wikidata.org/wiki/Q960570","display_name":"Traffic congestion reconstruction with Kerner's three-phase theory","level":3,"score":0.6615104079246521},{"id":"https://openalex.org/C2779888511","wikidata":"https://www.wikidata.org/wiki/Q244156","display_name":"Traffic congestion","level":2,"score":0.6521226167678833},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.5859001278877258},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.466656893491745},{"id":"https://openalex.org/C64093975","wikidata":"https://www.wikidata.org/wiki/Q356677","display_name":"Floating car data","level":3,"score":0.4555538594722748},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43786129355430603},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.4253098666667938},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40903428196907043},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3587588369846344},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28380119800567627},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.23903679847717285},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1546666920185089},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.15268856287002563},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09578371047973633},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09271568059921265},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3149059","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3149059","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09703355.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fd904c1f12504b3b9a209281a6f69854","is_oa":true,"landing_page_url":"https://doaj.org/article/fd904c1f12504b3b9a209281a6f69854","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 16123-16133 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3149059","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3149059","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09703355.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.800000011920929,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4210431740.pdf","grobid_xml":"https://content.openalex.org/works/W4210431740.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W2003924793","https://openalex.org/W2015189589","https://openalex.org/W2038436579","https://openalex.org/W2296760620","https://openalex.org/W2318975454","https://openalex.org/W2586322860","https://openalex.org/W2591142659","https://openalex.org/W2623443911","https://openalex.org/W2736193149","https://openalex.org/W2743623239","https://openalex.org/W2785818537","https://openalex.org/W2947430130","https://openalex.org/W2993383518","https://openalex.org/W3000197461","https://openalex.org/W3001232759","https://openalex.org/W3002262402","https://openalex.org/W3006377662","https://openalex.org/W3040906473","https://openalex.org/W3086811561","https://openalex.org/W3092715283","https://openalex.org/W3101353331","https://openalex.org/W3101421508","https://openalex.org/W3105469237","https://openalex.org/W3110474526","https://openalex.org/W3114937261","https://openalex.org/W3128581656","https://openalex.org/W3134341229","https://openalex.org/W6714895396"],"related_works":["https://openalex.org/W2972320057","https://openalex.org/W4220875044","https://openalex.org/W4386289889","https://openalex.org/W2074943018","https://openalex.org/W2945875309","https://openalex.org/W3117279048","https://openalex.org/W4206269847","https://openalex.org/W2898775471","https://openalex.org/W2587362999","https://openalex.org/W1977405947"],"abstract_inverted_index":{"Traffic":[0,34,119],"congestion":[1,13,41,49,106,195],"affects":[2],"quality":[3],"of":[4,40,51,126,130,150,163],"life":[5],"by":[6,196],"inducing":[7],"frustration":[8],"and":[9,56,68,74,86,135],"wasting":[10],"time.":[11],"The":[12,137,189],"is":[14,69,140,147],"also":[15],"critical":[16],"to":[17,30,200],"vehicles":[18],"with":[19,71],"high":[20],"emergencies":[21],"such":[22,91],"as":[23],"ambulances":[24],"or":[25],"police":[26],"cars.":[27],"This":[28],"leads":[29],"additional":[31],"CO2":[32],"emissions.":[33],"management":[35],"requires":[36],"the":[37,48,72,127,143,173,178,198],"accurate":[38,182],"modeling":[39,90],"levels.":[42],"Two":[43],"main":[44],"observable":[45],"parameters":[46,120],"identify":[47],"state":[50],"a":[52,65,96,113,148,161],"city:":[53],"vehicle":[54,151],"speed":[55],"density.":[57],"Congestion":[58],"has":[59],"an":[60,84],"intuitive":[61],"definition":[62],"rather":[63],"than":[64],"quantitative":[66],"one,":[67],"associated":[70],"disorder":[73],"randomness":[75],"occurring":[76],"in":[77,155,158],"traffic":[78,109,152,194],"parameters.":[79],"Therefore,":[80],"statistical":[81],"analysis":[82],"offers":[83],"efficient":[85],"natural":[87],"framework":[88],"for":[89,101,166,185],"disorders.":[92],"In":[93],"this":[94],"study,":[95],"differential-entropy-based":[97],"approach":[98,180],"was":[99,117],"proposed":[100,138,179,190],"labelling":[102],"purposes.":[103],"Subsequently,":[104],"supervised":[105],"prediction":[107,183],"from":[108],"meta-parameters":[110],"based":[111],"on":[112,142,172],"convolutional":[114],"neural":[115],"network":[116],"proposed.":[118],"includes":[121],"node":[122],"localization,":[123],"date,":[124],"day":[125],"week,":[128],"time":[129],"day,":[131],"special":[132],"road":[133],"conditions,":[134],"holidays.":[136],"model":[139],"validated":[141],"CityPulse":[144,174],"dataset,":[145],"which":[146],"set":[149],"records,":[153],"collected":[154],"Aarhus":[156],"city":[157],"Denmark":[159],"over":[160],"period":[162],"six":[164],"months,":[165],"449":[167],"observation":[168],"nodes.":[169],"Simulation":[170],"results":[171],"dataset":[175],"illustrate":[176],"that":[177],"yields":[181],"rates":[184],"different":[186],"nodes":[187],"considered.":[188],"system":[191],"can":[192],"prevent":[193],"reorienting":[197],"drivers":[199],"follow":[201],"other":[202],"itineraries.":[203]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":8}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}
