{"id":"https://openalex.org/W4413225211","doi":"https://doi.org/10.3390/ijgi14080308","title":"A Spatiotemporal Multi-Model Ensemble Framework for Urban Multimodal Traffic Flow Prediction","display_name":"A Spatiotemporal Multi-Model Ensemble Framework for Urban Multimodal Traffic Flow Prediction","publication_year":2025,"publication_date":"2025-08-10","ids":{"openalex":"https://openalex.org/W4413225211","doi":"https://doi.org/10.3390/ijgi14080308"},"language":"en","primary_location":{"id":"doi:10.3390/ijgi14080308","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi14080308","pdf_url":"https://www.mdpi.com/2220-9964/14/8/308/pdf","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2220-9964/14/8/308/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076082106","display_name":"Zhenkai Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenkai Wang","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016749325","display_name":"Lujin Hu","orcid":"https://orcid.org/0000-0003-1465-7006"},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lujin Hu","raw_affiliation_strings":["School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 102616, China","institution_ids":["https://openalex.org/I62853816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5016749325"],"corresponding_institution_ids":["https://openalex.org/I62853816"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":2.1983,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.87421662,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"14","issue":"8","first_page":"308","last_page":"308"},"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":0.9991000294685364,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8062582015991211},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.5804291367530823},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5640581250190735},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5206729173660278},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4392159581184387},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.4299643337726593},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4152098298072815},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.41039833426475525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37034282088279724},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3304576873779297},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.10854968428611755},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07840904593467712}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8062582015991211},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.5804291367530823},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5640581250190735},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5206729173660278},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4392159581184387},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.4299643337726593},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4152098298072815},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.41039833426475525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37034282088279724},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3304576873779297},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.10854968428611755},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07840904593467712},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/ijgi14080308","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi14080308","pdf_url":"https://www.mdpi.com/2220-9964/14/8/308/pdf","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e18b6c5de00c4846a6d34c25614feb31","is_oa":true,"landing_page_url":"https://doaj.org/article/e18b6c5de00c4846a6d34c25614feb31","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":"ISPRS International Journal of Geo-Information, Vol 14, Iss 8, p 308 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/ijgi14080308","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi14080308","pdf_url":"https://www.mdpi.com/2220-9964/14/8/308/pdf","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320325174","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4413225211.pdf"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1990816055","https://openalex.org/W2004353783","https://openalex.org/W2024558842","https://openalex.org/W2036785686","https://openalex.org/W2070678348","https://openalex.org/W2079662306","https://openalex.org/W2097498150","https://openalex.org/W2125817951","https://openalex.org/W2132711183","https://openalex.org/W2166813035","https://openalex.org/W2563118655","https://openalex.org/W2583466634","https://openalex.org/W2593239008","https://openalex.org/W2613331518","https://openalex.org/W2775717462","https://openalex.org/W2901504064","https://openalex.org/W2921685418","https://openalex.org/W2964319113","https://openalex.org/W3027664001","https://openalex.org/W3082472395","https://openalex.org/W3109254449","https://openalex.org/W3135400423","https://openalex.org/W3154325244","https://openalex.org/W3164133347","https://openalex.org/W3169575318","https://openalex.org/W3183801287","https://openalex.org/W3185889262","https://openalex.org/W3193007873","https://openalex.org/W4200634602","https://openalex.org/W4210789062","https://openalex.org/W4367595602","https://openalex.org/W4385287316","https://openalex.org/W4387846860","https://openalex.org/W4392247425","https://openalex.org/W4398142516","https://openalex.org/W4403123483","https://openalex.org/W4405920714","https://openalex.org/W4405945374","https://openalex.org/W6659849045","https://openalex.org/W6855354483"],"related_works":["https://openalex.org/W2015747722","https://openalex.org/W2362050182","https://openalex.org/W2382418233","https://openalex.org/W2369897927","https://openalex.org/W3031731056","https://openalex.org/W4327918537","https://openalex.org/W4293167957","https://openalex.org/W2361035307","https://openalex.org/W2380455807","https://openalex.org/W3007866289"],"abstract_inverted_index":{"Urban":[0],"multimodal":[1,154],"travel":[2,25,78,93,155],"trajectory":[3,44,67],"prediction":[4],"is":[5,54],"a":[6,48,85,118],"core":[7],"challenge":[8],"in":[9,40],"Intelligent":[10],"Transportation":[11],"Systems":[12],"(ITSs).":[13],"It":[14],"requires":[15],"modeling":[16],"both":[17],"spatiotemporal":[18,49,119,149],"dependencies":[19],"and":[20,31,61,79,95,115,150,157,169],"dynamic":[21,77,92],"interactions":[22],"among":[23],"different":[24],"modes":[26],"such":[27],"as":[28],"taxi,":[29],"bike-sharing,":[30],"buses.":[32],"To":[33],"address":[34],"the":[35,66,106],"limitations":[36],"of":[37,108,125],"existing":[38],"methods":[39],"capturing":[41],"these":[42,109],"diverse":[43],"characteristics,":[45],"we":[46,83],"propose":[47],"multi-model":[50],"ensemble":[51,56],"framework,":[52],"which":[53],"an":[55],"model":[57,71,102],"called":[58],"GLEN":[59],"(GCN":[60],"LSTM":[62],"Ensemble":[63],"Network).":[64],"Firstly,":[65],"feature":[68],"adaptive":[69],"driven":[70],"selection":[72],"mechanism":[73],"classifies":[74],"trajectories":[75,156],"into":[76],"fixed-route":[80,103],"scenarios.":[81],"Secondly,":[82],"use":[84],"Graph":[86],"Convolutional":[87],"Network":[88],"(GCN)":[89],"to":[90,101,121],"capture":[91],"patterns":[94],"Long":[96],"Short-Term":[97],"Memory":[98],"(LSTM)":[99],"network":[100],"patterns.":[104],"Subsequently":[105],"outputs":[107],"models":[110],"are":[111],"dynamically":[112],"weighted,":[113],"integrated,":[114],"fused":[116],"over":[117],"grid":[120],"produce":[122],"accurate":[123],"forecasts":[124],"urban":[126,166],"total":[127],"traffic":[128,167],"flow":[129],"at":[130],"multiple":[131],"future":[132],"time":[133],"steps.":[134],"Finally,":[135],"experimental":[136],"validation":[137],"using":[138],"Beijing\u2019s":[139],"Chaoyang":[140],"district":[141],"datasets":[142],"demonstrates":[143],"that":[144],"our":[145],"framework":[146],"effectively":[147],"captures":[148],"interactive":[151],"characteristics":[152],"between":[153],"outperforms":[158],"mainstream":[159],"baselines,":[160],"thereby":[161],"offering":[162],"robust":[163],"support":[164],"for":[165],"management":[168],"planning.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-12T08:23:45.883708","created_date":"2025-10-10T00:00:00"}