{"id":"https://openalex.org/W4400647789","doi":"https://doi.org/10.1109/iv55156.2024.10588573","title":"Interconnected Traffic Forecasting Using Time Distributed Encoder-Decoder Multivariate Multi-Step LSTM","display_name":"Interconnected Traffic Forecasting Using Time Distributed Encoder-Decoder Multivariate Multi-Step LSTM","publication_year":2024,"publication_date":"2024-06-02","ids":{"openalex":"https://openalex.org/W4400647789","doi":"https://doi.org/10.1109/iv55156.2024.10588573"},"language":"en","primary_location":{"id":"doi:10.1109/iv55156.2024.10588573","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv55156.2024.10588573","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","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/A5083661869","display_name":"Sifatul Mostafi","orcid":"https://orcid.org/0000-0002-2794-9035"},"institutions":[{"id":"https://openalex.org/I39470171","display_name":"Ontario Tech University","ror":"https://ror.org/016zre027","country_code":"CA","type":"education","lineage":["https://openalex.org/I39470171"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sifatul Mostafi","raw_affiliation_strings":["Ontario Tech University,IoT Research Laboratory,ECSE Department,Oshawa,ON,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ontario Tech University,IoT Research Laboratory,ECSE Department,Oshawa,ON,Canada","institution_ids":["https://openalex.org/I39470171"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074020510","display_name":"Taghreed Alghamdi","orcid":"https://orcid.org/0000-0002-5640-3824"},"institutions":[{"id":"https://openalex.org/I39470171","display_name":"Ontario Tech University","ror":"https://ror.org/016zre027","country_code":"CA","type":"education","lineage":["https://openalex.org/I39470171"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Taghreed Alghamdi","raw_affiliation_strings":["Ontario Tech University,IoT Research Laboratory,ECSE Department,Oshawa,ON,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ontario Tech University,IoT Research Laboratory,ECSE Department,Oshawa,ON,Canada","institution_ids":["https://openalex.org/I39470171"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026935022","display_name":"Khalid Elgazzar","orcid":"https://orcid.org/0000-0002-5892-632X"},"institutions":[{"id":"https://openalex.org/I39470171","display_name":"Ontario Tech University","ror":"https://ror.org/016zre027","country_code":"CA","type":"education","lineage":["https://openalex.org/I39470171"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Khalid Elgazzar","raw_affiliation_strings":["Ontario Tech University,IoT Research Laboratory,ECSE Department,Oshawa,ON,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ontario Tech University,IoT Research Laboratory,ECSE Department,Oshawa,ON,Canada","institution_ids":["https://openalex.org/I39470171"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1681,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.76338398,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2503","last_page":"2508"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9908999800682068,"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":0.9908999800682068,"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/T10320","display_name":"Neural Networks and Applications","score":0.9646999835968018,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9168000221252441,"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/computer-science","display_name":"Computer science","score":0.736306369304657},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.7000303864479065},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6702144145965576},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.46511414647102356},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4217302203178406},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22648227214813232},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.06871488690376282}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.736306369304657},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.7000303864479065},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6702144145965576},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.46511414647102356},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4217302203178406},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22648227214813232},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.06871488690376282}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv55156.2024.10588573","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv55156.2024.10588573","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2573587735","https://openalex.org/W2775717462","https://openalex.org/W2792440155","https://openalex.org/W2907228515","https://openalex.org/W2907637692","https://openalex.org/W2942521752","https://openalex.org/W2955168531","https://openalex.org/W2977656904","https://openalex.org/W3003862857","https://openalex.org/W3008996014","https://openalex.org/W3046773429","https://openalex.org/W3120726020","https://openalex.org/W3171254206","https://openalex.org/W3208660104","https://openalex.org/W3213856876","https://openalex.org/W3216589098","https://openalex.org/W4312427403"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Long":[0],"Short-term":[1],"Memory":[2],"(LSTM)":[3],"is":[4,11],"a":[5,115],"Recurrent":[6],"Neural":[7],"Network":[8],"(RNN)":[9],"that":[10,176],"widely":[12],"used":[13],"in":[14,28,44,76,104,158,191],"time":[15,32],"series":[16,33],"traffic":[17,50,58,73,91,101,122,132,144,181],"forecasting.":[18,133],"LSTM":[19],"captures":[20],"both":[21,75,103,190],"short-term":[22,106,121,193],"and":[23,26,64,69,71,79,97,109,142,162,169,194],"long-term":[24,110,131],"trends":[25],"dependency":[27],"sequential":[29],"data":[30],"like":[31],"data,":[34],"as":[35,124],"it":[36],"contains":[37],"specialized":[38],"memory":[39,45],"cells":[40],"to":[41,55,88,118,126,129],"store":[42],"information":[43],"for":[46,147],"longer":[47],"periods.":[48],"Existing":[49],"forecasting":[51,74,102,123,146],"approaches":[52],"lack":[53],"features":[54],"forecast":[56,180],"the":[57,77,90,105,120,127,166,177,192,195],"speed":[59,92,145,182],"of":[60,93],"interconnected":[61,94,139,184],"road":[62,95,140,185],"links":[63,96,141,186],"provide":[65,98],"multivariate":[66,99],"(i.e.,":[67],"multi-input":[68],"multi-output)":[70],"multi-step":[72],"short-":[78],"long-term.":[80,196],"We":[81,113,151],"propose":[82],"an":[83,156],"Encoder-Decoder":[84],"LSTM-based":[85],"sequence-to-sequence":[86],"architecture":[87],"capture":[89],"multistep":[100],"(15":[107],"minutes)":[108],"(two":[111],"days).":[112],"apply":[114],"sliding-window":[116],"approach":[117],"feed":[119],"input":[125],"model":[128,135,178],"project":[130],"Our":[134],"can":[136,179],"incorporate":[137],"multiple":[138,148],"providing":[143],"future":[149],"steps.":[150],"conducted":[152],"our":[153],"experiment":[154],"at":[155],"intersection":[157],"Oshawa,":[159],"ON,":[160],"Canada,":[161],"evaluated":[163],"performance":[164],"using":[165],"error":[167],"distribution":[168],"Mean":[170],"Absolute":[171],"Error.":[172],"The":[173],"evaluation":[174],"shows":[175],"across":[183],"with":[187],"negligible":[188],"error,":[189]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}