{"id":"https://openalex.org/W4308694605","doi":"https://doi.org/10.3390/s22228678","title":"Research on Satellite Network Traffic Prediction Based on Improved GRU Neural Network","display_name":"Research on Satellite Network Traffic Prediction Based on Improved GRU Neural Network","publication_year":2022,"publication_date":"2022-11-10","ids":{"openalex":"https://openalex.org/W4308694605","doi":"https://doi.org/10.3390/s22228678","pmid":"https://pubmed.ncbi.nlm.nih.gov/36433276"},"language":"en","primary_location":{"id":"doi:10.3390/s22228678","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22228678","pdf_url":"https://www.mdpi.com/1424-8220/22/22/8678/pdf?version=1668069367","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/22/22/8678/pdf?version=1668069367","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100636194","display_name":"Zhiguo Liu","orcid":"https://orcid.org/0000-0003-0280-5040"},"institutions":[{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiguo Liu","raw_affiliation_strings":["Communication and Network Laboratory, Dalian University, Dalian 116622, China"],"raw_orcid":"https://orcid.org/0000-0003-0280-5040","affiliations":[{"raw_affiliation_string":"Communication and Network Laboratory, Dalian University, Dalian 116622, China","institution_ids":["https://openalex.org/I4210092944"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447968","display_name":"Weijie Li","orcid":"https://orcid.org/0000-0002-7049-2851"},"institutions":[{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijie Li","raw_affiliation_strings":["Communication and Network Laboratory, Dalian University, Dalian 116622, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication and Network Laboratory, Dalian University, Dalian 116622, China","institution_ids":["https://openalex.org/I4210092944"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101591493","display_name":"Jianxin Feng","orcid":"https://orcid.org/0000-0002-3780-6863"},"institutions":[{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxin Feng","raw_affiliation_strings":["Communication and Network Laboratory, Dalian University, Dalian 116622, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication and Network Laboratory, Dalian University, Dalian 116622, China","institution_ids":["https://openalex.org/I4210092944"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100747006","display_name":"Jiaojiao Zhang","orcid":"https://orcid.org/0000-0002-6084-5502"},"institutions":[{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaojiao Zhang","raw_affiliation_strings":["Communication and Network Laboratory, Dalian University, Dalian 116622, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication and Network Laboratory, Dalian University, Dalian 116622, China","institution_ids":["https://openalex.org/I4210092944"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100636194"],"corresponding_institution_ids":["https://openalex.org/I4210092944"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":3.562,"has_fulltext":true,"cited_by_count":37,"citation_normalized_percentile":{"value":0.93106922,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"22","issue":"22","first_page":"8678","last_page":"8678"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9988999962806702,"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":0.9988999962806702,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6447715759277344},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.6445401906967163},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6102017164230347},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.6095597743988037},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5847035646438599},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.575333833694458},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5665799379348755},{"id":"https://openalex.org/keywords/network-traffic-simulation","display_name":"Network traffic simulation","score":0.5544933080673218},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.5230618119239807},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4448367953300476},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4294188618659973},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36954036355018616},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.2690567672252655},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.23640483617782593},{"id":"https://openalex.org/keywords/network-traffic-control","display_name":"Network traffic control","score":0.1570388376712799}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6447715759277344},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.6445401906967163},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6102017164230347},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.6095597743988037},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5847035646438599},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.575333833694458},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5665799379348755},{"id":"https://openalex.org/C94168897","wikidata":"https://www.wikidata.org/wiki/Q574324","display_name":"Network traffic simulation","level":4,"score":0.5544933080673218},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.5230618119239807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4448367953300476},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4294188618659973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36954036355018616},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.2690567672252655},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.23640483617782593},{"id":"https://openalex.org/C201100257","wikidata":"https://www.wikidata.org/wiki/Q393287","display_name":"Network traffic control","level":3,"score":0.1570388376712799},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.3390/s22228678","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22228678","pdf_url":"https://www.mdpi.com/1424-8220/22/22/8678/pdf?version=1668069367","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},{"id":"pmid:36433276","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36433276","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:af745dce533b4035bf61e690e77059f6","is_oa":true,"landing_page_url":"https://doaj.org/article/af745dce533b4035bf61e690e77059f6","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":"Sensors, Vol 22, Iss 22, p 8678 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/22/22/8678/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s22228678","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 22; Issue 22; Pages: 8678","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9699114","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9699114","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s22228678","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s22228678","pdf_url":"https://www.mdpi.com/1424-8220/22/22/8678/pdf?version=1668069367","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"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":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4308694605.pdf","grobid_xml":"https://content.openalex.org/works/W4308694605.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1576278180","https://openalex.org/W1967822773","https://openalex.org/W2062864198","https://openalex.org/W2419554616","https://openalex.org/W2528824243","https://openalex.org/W2740570963","https://openalex.org/W2806991962","https://openalex.org/W2891969803","https://openalex.org/W2917442832","https://openalex.org/W2921139866","https://openalex.org/W2945810026","https://openalex.org/W2963358003","https://openalex.org/W2982197838","https://openalex.org/W3019777957","https://openalex.org/W3036681881","https://openalex.org/W3040172617","https://openalex.org/W3082131213","https://openalex.org/W3088014635","https://openalex.org/W3094568574","https://openalex.org/W3115924527","https://openalex.org/W3118343079","https://openalex.org/W3123006215","https://openalex.org/W3190256259","https://openalex.org/W3202235298","https://openalex.org/W4210906547","https://openalex.org/W6633706346"],"related_works":["https://openalex.org/W2374980776","https://openalex.org/W2382692540","https://openalex.org/W2385916660","https://openalex.org/W3195411348","https://openalex.org/W1963878606","https://openalex.org/W2378981629","https://openalex.org/W1993870076","https://openalex.org/W2392968384","https://openalex.org/W2386286405","https://openalex.org/W2079613190"],"abstract_inverted_index":{"The":[0],"current":[1],"satellite":[2,14,36],"network":[3,21,37,113],"traffic":[4,15,22,38,68,77,135],"forecasting":[5,23,27,39],"methods":[6],"cannot":[7],"fully":[8,58],"exploit":[9],"the":[10,51,60,74,83,91,99,111,118,125,129,138,149],"long":[11,65],"correlation":[12,66],"between":[13],"sequences,":[16,70,88],"which":[17],"leads":[18],"to":[19,73,97,109],"large":[20],"errors":[24,139],"and":[25,64,79,89,116,137,145,155],"low":[26],"accuracy.":[28,101],"To":[29],"solve":[30],"these":[31],"problems,":[32],"we":[33],"propose":[34],"a":[35],"method":[40,49,127],"with":[41,54,133,148],"an":[42],"improved":[43],"gate":[44],"recurrent":[45],"unit":[46],"(GRU).":[47],"This":[48],"combines":[50],"attention":[52,72],"mechanism":[53],"GRU":[55],"neural":[56],"network,":[57],"mines":[59,90],"characteristics":[61,85,93],"of":[62,76,86,94],"self-similarity":[63],"among":[67],"data":[69,78,95],"pays":[71],"importance":[75],"hidden":[80],"state,":[81],"learns":[82],"time-dependent":[84],"input":[87],"interdependent":[92],"sequences":[96],"improve":[98,117],"prediction":[100,119],"Particle":[102],"Swarm":[103],"Optimization":[104],"(PSO)":[105],"algorithm":[106],"is":[107],"used":[108],"obtain":[110],"best":[112,130],"model":[114],"Hyperparameter":[115],"efficiency.":[120],"Simulation":[121],"results":[122],"show":[123],"that":[124],"proposed":[126],"has":[128],"fitting":[131],"effect":[132],"real":[134],"data,":[136],"are":[140],"reduced":[141],"by":[142],"26.9%,":[143],"37.2%,":[144],"57.8%":[146],"compared":[147],"GRU,":[150],"Support":[151],"Vector":[152],"Machine":[153],"(SVM),":[154],"Fractional":[156],"Autoregressive":[157],"Integration":[158],"Moving":[159],"Average":[160],"(FARIMA)":[161],"models,":[162],"respectively.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":11}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
