{"id":"https://openalex.org/W4400277308","doi":"https://doi.org/10.1109/wcnc57260.2024.10570573","title":"Spatio-Temporal Multi-View Based Short-Term Traffic Forecasting for Incomplete Time Series in LEO Satellite Networks","display_name":"Spatio-Temporal Multi-View Based Short-Term Traffic Forecasting for Incomplete Time Series in LEO Satellite Networks","publication_year":2024,"publication_date":"2024-04-21","ids":{"openalex":"https://openalex.org/W4400277308","doi":"https://doi.org/10.1109/wcnc57260.2024.10570573"},"language":"en","primary_location":{"id":"doi:10.1109/wcnc57260.2024.10570573","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/wcnc57260.2024.10570573","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Wireless Communications and Networking Conference (WCNC)","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":"https://openalex.org/A5111550220","display_name":"Liang Peng","orcid":null},"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":"Liang Peng","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China,100876"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101437836","display_name":"Jie Yan","orcid":"https://orcid.org/0000-0001-9512-322X"},"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":"Jie Yan","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China,100876"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065855043","display_name":"Binquan Guo","orcid":"https://orcid.org/0000-0002-0660-1830"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binquan Guo","raw_affiliation_strings":["Xidian University,State Key Laboratory of Integrated Service Networks,Xi&#x0027;an,P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University,State Key Laboratory of Integrated Service Networks,Xi&#x0027;an,P.R.China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100679196","display_name":"Xiaoxiang Wang","orcid":"https://orcid.org/0000-0002-2924-2295"},"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":"Xiaoxiang Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,Beijing,China,100876"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,Beijing,China,100876","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":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.991100013256073,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.991100013256073,"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":0.988099992275238,"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"}},{"id":"https://openalex.org/T14280","display_name":"Big Data Technologies and Applications","score":0.979200005531311,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.7435874938964844},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7032384872436523},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6572033166885376},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.6170469522476196},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5804488658905029},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.37755951285362244},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3573009669780731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32601216435432434},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2041178047657013},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13820600509643555},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09397497773170471},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08329936861991882},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.06383728981018066}],"concepts":[{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.7435874938964844},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7032384872436523},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6572033166885376},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.6170469522476196},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5804488658905029},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.37755951285362244},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3573009669780731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32601216435432434},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2041178047657013},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13820600509643555},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09397497773170471},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08329936861991882},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.06383728981018066},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcnc57260.2024.10570573","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/wcnc57260.2024.10570573","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Wireless Communications and Networking Conference (WCNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8304522762","display_name":null,"funder_award_id":"2018YFC1504502","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2038393123","https://openalex.org/W2187289506","https://openalex.org/W2957283398","https://openalex.org/W2964010366","https://openalex.org/W3009683580","https://openalex.org/W3014693308","https://openalex.org/W3045628664","https://openalex.org/W3092220725","https://openalex.org/W3129054759","https://openalex.org/W3157761116","https://openalex.org/W3213342743","https://openalex.org/W4285153164","https://openalex.org/W4293812275","https://openalex.org/W4312312028","https://openalex.org/W4312980503","https://openalex.org/W4387870834","https://openalex.org/W6720065314","https://openalex.org/W6759080752"],"related_works":["https://openalex.org/W42295635","https://openalex.org/W1973996291","https://openalex.org/W1919101720","https://openalex.org/W2330575325","https://openalex.org/W2163803519","https://openalex.org/W2497592525","https://openalex.org/W3096145648","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Accurate":[0],"short-term":[1],"traffic":[2,35,43,52,83,173,180,185],"forecasting":[3],"is":[4],"essential":[5],"to":[6,21,78,104,114,139,167,194,204],"improve":[7,79],"the":[8,30,34,49,80,87,99,106,116,141,151,161,189,205],"efficiency":[9],"of":[10,51,82,91,164,171,178,210],"data":[11],"transmission":[12,24],"in":[13,29,58,208],"Low":[14],"Earth":[15],"Orbit":[16],"(LEO)":[17],"satellite":[18,92],"networks.":[19],"Due":[20],"collector":[22],"failures,":[23],"errors":[25],"and":[26,159,175],"memory":[27,135],"failures":[28],"complex":[31],"space":[32],"environment,":[33],"value":[36],"absence":[37],"phenomenon":[38],"may":[39],"occur.":[40],"However,":[41],"in-complete":[42],"time":[44,76,112],"series":[45,77,113],"can":[46],"significantly":[47],"reduce":[48],"accuracy":[50,81],"forecasting.":[53],"To":[54],"overcome":[55],"this":[56,59,96,124,165],"problem,":[57],"work,":[60],"we":[61,149],"propose":[62],"a":[63,120,127,134,145],"novel":[64],"Spatio-":[65],"Temporal":[66],"Multi-view":[67],"based":[68],"Short-term":[69],"Traffic":[70],"Forecasting":[71],"(STMV-STF)":[72],"model":[73,97,125,166,191,207],"for":[74],"incomplete":[75],"prediction":[84],"by":[85],"combining":[86],"unique":[88],"spatio-temporal":[89],"correlation":[90,102],"network":[93],"traffic.":[94],"Specifically,":[95],"utilizes":[98,126],"time-lagged":[100],"pearson":[101],"equation":[103],"select":[105],"<tex":[107],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[108],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$k$</tex>":[109],"most":[110],"correlated":[111],"impute":[115,140],"missing":[117,142,152,172,200],"values":[118,143,153,174],"from":[119,144,155],"spatial":[121],"view.":[122,147],"Meanwhile,":[123],"proposed":[128],"gated":[129],"recurrent":[130],"unit":[131],"(GRU)":[132],"with":[133],"decay":[136],"gate":[137],"(MG-GRU)":[138],"temporal":[146],"Finally,":[148],"aggregate":[150],"imputed":[154],"these":[156],"two":[157],"views":[158],"design":[160],"training":[162],"process":[163],"enable":[168],"online":[169],"imputation":[170],"real-time":[176],"output":[177],"predicted":[179],"values.":[181],"Experiments":[182],"on":[183],"real":[184],"datasets":[186],"show":[187],"that":[188],"STMV-STF":[190],"achieves":[192],"19.86%":[193],"33.46%":[195],"error":[196,214],"reduction":[197],"under":[198],"different":[199],"rate":[201],"conditions":[202],"compared":[203],"baseline":[206],"terms":[209],"root":[211],"mean":[212],"square":[213],"(RMSE)":[215],"metric.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}