{"id":"https://openalex.org/W4410858634","doi":"https://doi.org/10.1145/3708657.3708678","title":"Traffic Flow Prediction Based on Spatiotemporal Feature Fusion for 5G-R Networks","display_name":"Traffic Flow Prediction Based on Spatiotemporal Feature Fusion for 5G-R Networks","publication_year":2024,"publication_date":"2024-11-21","ids":{"openalex":"https://openalex.org/W4410858634","doi":"https://doi.org/10.1145/3708657.3708678"},"language":"en","primary_location":{"id":"doi:10.1145/3708657.3708678","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3708657.3708678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 10th International Conference on Communication and Information Processing","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":null,"display_name":"Ran Zhang","orcid":"https://orcid.org/0009-0002-1895-9538"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Zhang","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Communications, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-1895-9538","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Communications, Beijing, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yiran Zhao","orcid":"https://orcid.org/0009-0007-6811-4521"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiran Zhao","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Communications, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0007-6811-4521","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Communications, Beijing, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048802154","display_name":"Danpu Liu","orcid":"https://orcid.org/0000-0003-4296-5209"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danpu Liu","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Communications, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4296-5209","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Communications, Beijing, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074945572","display_name":"Jufeng Fei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210105312","display_name":"Shanghai Power Equipment Research Institute","ror":"https://ror.org/01pw44479","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210105312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jufeng Fei","raw_affiliation_strings":["Shanghai Radio Equipment Research Institute, Shanghai, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0001-4621-8908","affiliations":[{"raw_affiliation_string":"Shanghai Radio Equipment Research Institute, Shanghai, Shanghai, China","institution_ids":["https://openalex.org/I4210105312"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mingqi Li","orcid":"https://orcid.org/0009-0001-5000-3619"},"institutions":[{"id":"https://openalex.org/I4210105312","display_name":"Shanghai Power Equipment Research Institute","ror":"https://ror.org/01pw44479","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210105312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingqi Li","raw_affiliation_strings":["Shanghai Radio Equipment Research Institute, Shanghai, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0001-5000-3619","affiliations":[{"raw_affiliation_string":"Shanghai Radio Equipment Research Institute, Shanghai, Shanghai, China","institution_ids":["https://openalex.org/I4210105312"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101764889","display_name":"Zhilong Zhang","orcid":"https://orcid.org/0000-0002-9328-9098"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhilong Zhang","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Communications, Beijing, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9328-9098","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Communications, Beijing, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"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":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"130","last_page":"136"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9746999740600586,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9703999757766724,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.6779451370239258},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5387976765632629},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5257335901260376},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.509680986404419},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4617718458175659},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43026214838027954},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09599897265434265}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6779451370239258},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5387976765632629},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5257335901260376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.509680986404419},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4617718458175659},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43026214838027954},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09599897265434265},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3708657.3708678","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3708657.3708678","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 10th International Conference on Communication and Information Processing","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":8,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2789386460","https://openalex.org/W2807536558","https://openalex.org/W2969210779","https://openalex.org/W3035338169","https://openalex.org/W3040172617","https://openalex.org/W4210392813","https://openalex.org/W4289655102"],"related_works":["https://openalex.org/W3147584709","https://openalex.org/W2099421762","https://openalex.org/W2530546662","https://openalex.org/W2967030268","https://openalex.org/W2977677679","https://openalex.org/W2185253430","https://openalex.org/W1992327129","https://openalex.org/W4210345652","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Precise":[0],"traffic":[1,18,41,83,97,139],"flow":[2,42,84],"prediction":[3,46,69,135],"is":[4,115],"the":[5,29,40,76,82,89,96,128,134],"premise":[6],"of":[7,81,105,137],"energy-saving":[8],"control":[9],"in":[10,15,19,55,85],"5G":[11],"networks.":[12,87],"However,":[13],"unlike":[14],"public":[16],"networks,":[17,109],"5G-R":[20,56,86,138],"networks":[21,50],"has":[22],"many":[23],"spikes":[24],"and":[25,33,79,92,107,149,161],"closely":[26],"relates":[27],"to":[28,39,74],"train":[30],"departure":[31],"direction":[32],"timetable,":[34],"which":[35],"brings":[36],"great":[37],"challenge":[38],"prediction.":[43],"The":[44,111,123,143],"existing":[45],"methods":[47],"for":[48,154],"cellular":[49],"cannot":[51],"achieve":[52],"satisfactory":[53],"performance":[54],"scenario.":[57],"To":[58],"address":[59],"this":[60],"issue,":[61],"we":[62],"propose":[63],"a":[64],"spatiotemporal":[65,77,93],"feature":[66,118],"fusion":[67,119],"based":[68],"model":[70,130],"that":[71,127],"enables":[72],"us":[73],"capture":[75],"correlation":[78],"periodicity":[80],"In":[88],"model,":[90],"time":[91],"features":[94],"among":[95],"are":[98,157],"separately":[99],"extracts":[100],"via":[101],"two":[102],"modules":[103],"consisting":[104],"LSTM":[106],"CNN-LSTM":[108],"respectively.":[110,163],"final":[112],"predicted":[113],"value":[114],"obtained":[116],"after":[117],"with":[120,141],"attention":[121],"mechanism.":[122],"experimental":[124],"results":[125],"show":[126],"proposed":[129],"can":[131],"significantly":[132],"improve":[133],"accuracy":[136],"compared":[140],"baselines.":[142],"root":[144],"mean":[145,150],"square":[146],"error":[147,152],"(RMSE)":[148],"absolute":[151],"(MAE)":[153],"non-stopping":[155],"stations":[156],"reduced":[158],"by":[159],"76%":[160],"66%,":[162]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
