{"id":"https://openalex.org/W2807536558","doi":"https://doi.org/10.1109/lcomm.2018.2841832","title":"Citywide Cellular Traffic Prediction Based on Densely Connected Convolutional Neural Networks","display_name":"Citywide Cellular Traffic Prediction Based on Densely Connected Convolutional Neural Networks","publication_year":2018,"publication_date":"2018-05-29","ids":{"openalex":"https://openalex.org/W2807536558","doi":"https://doi.org/10.1109/lcomm.2018.2841832","mag":"2807536558"},"language":"en","primary_location":{"id":"doi:10.1109/lcomm.2018.2841832","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2018.2841832","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-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/A5045797640","display_name":"Chuanting Zhang","orcid":"https://orcid.org/0000-0002-6685-4071"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanting Zhang","raw_affiliation_strings":["Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-6685-4071","affiliations":[{"raw_affiliation_string":"Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100375622","display_name":"Haixia Zhang","orcid":"https://orcid.org/0000-0001-5081-7287"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haixia Zhang","raw_affiliation_strings":["Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0001-5081-7287","affiliations":[{"raw_affiliation_string":"Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100518283","display_name":"Dongfeng Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongfeng Yuan","raw_affiliation_strings":["Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022775569","display_name":"Minggao Zhang","orcid":"https://orcid.org/0009-0001-0847-963X"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minggao Zhang","raw_affiliation_strings":["Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":17.1882,"has_fulltext":false,"cited_by_count":272,"citation_normalized_percentile":{"value":0.9958407,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"22","issue":"8","first_page":"1656","last_page":"1659"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9836999773979187,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9830999970436096,"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":0.7793874144554138},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6403745412826538},{"id":"https://openalex.org/keywords/cellular-traffic","display_name":"Cellular traffic","score":0.49982666969299316},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4831792414188385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4755246937274933},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46701082587242126},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.46439889073371887},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43526262044906616},{"id":"https://openalex.org/keywords/cellular-network","display_name":"Cellular network","score":0.42251861095428467},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.41334742307662964},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3640192747116089},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.22926664352416992},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.19783690571784973},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12176662683486938},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09717443585395813}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7793874144554138},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6403745412826538},{"id":"https://openalex.org/C133972139","wikidata":"https://www.wikidata.org/wiki/Q5058371","display_name":"Cellular traffic","level":3,"score":0.49982666969299316},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4831792414188385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4755246937274933},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46701082587242126},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.46439889073371887},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43526262044906616},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.42251861095428467},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.41334742307662964},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3640192747116089},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.22926664352416992},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.19783690571784973},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12176662683486938},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09717443585395813},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lcomm.2018.2841832","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lcomm.2018.2841832","pdf_url":null,"source":{"id":"https://openalex.org/S147316732","display_name":"IEEE Communications Letters","issn_l":"1089-7798","issn":["1089-7798","1558-2558","2373-7891"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310316002","host_organization_name":"IEEE Communications Society","host_organization_lineage":["https://openalex.org/P4310316002","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Communications Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Communications Letters","raw_type":"journal-article"},{"id":"pmh:oai:research-information.bris.ac.uk:publications/9afef219-126f-480a-b676-7062ea26b67d","is_oa":false,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/9afef219-126f-480a-b676-7062ea26b67d","pdf_url":null,"source":{"id":"https://openalex.org/S7407055359","display_name":"Explore Bristol Research","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Zhang, C, Zhang, H, Yuan, D & Zhang, M 2018, 'Citywide Cellular Traffic Prediction Based on Densely Connected Convolutional Neural Networks', IEEE Communications Letters. https://doi.org/10.1109/LCOMM.2018.2841832","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7799999713897705}],"awards":[{"id":"https://openalex.org/G3402875490","display_name":null,"funder_award_id":"61671278","funder_id":"https://openalex.org/F4320326181","funder_display_name":"National Aerospace Science Foundation of China"},{"id":"https://openalex.org/G683815681","display_name":null,"funder_award_id":"61622111","funder_id":"https://openalex.org/F4320326181","funder_display_name":"National Aerospace Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320326181","display_name":"National Aerospace Science Foundation of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W28713011","https://openalex.org/W2089549033","https://openalex.org/W2100495367","https://openalex.org/W2117829824","https://openalex.org/W2132559723","https://openalex.org/W2139111642","https://openalex.org/W2190432600","https://openalex.org/W2602923095","https://openalex.org/W2612472936","https://openalex.org/W2735105101","https://openalex.org/W2762605243","https://openalex.org/W2919115771","https://openalex.org/W2963389592","https://openalex.org/W2963446712","https://openalex.org/W6687472758"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W2748454020","https://openalex.org/W3119610945","https://openalex.org/W4306674287","https://openalex.org/W4287776258","https://openalex.org/W3027997911","https://openalex.org/W3021430260","https://openalex.org/W2995227436","https://openalex.org/W3011342776","https://openalex.org/W3128444563"],"abstract_inverted_index":{"With":[0],"accurate":[1],"traffic":[2,23,41,53],"prediction,":[3],"future":[4],"cellular":[5,22],"networks":[6],"can":[7,97],"make":[8],"self-management":[9],"and":[10,13,25,48,80],"embrace":[11],"intelligent":[12],"efficient":[14],"automation.":[15],"This":[16],"letter":[17],"devotes":[18],"itself":[19],"to":[20,31,73],"citywide":[21],"prediction":[24,88,107],"proposes":[26],"a":[27],"deep":[28],"learning":[29],"approach":[30],"model":[32],"the":[33,46,78,87,114],"nonlinear":[34],"dynamics":[35],"of":[36,51,77,92,117],"wireless":[37],"traffic.":[38],"By":[39],"treating":[40],"data":[42,115],"as":[43],"images,":[44],"both":[45],"spatial":[47,79],"temporal":[49,81],"dependence":[50],"cell":[52],"are":[54],"well":[55],"captured":[56],"utilizing":[57],"densely":[58],"connected":[59],"convolutional":[60],"neural":[61],"networks.":[62],"A":[63],"parametric":[64],"matrix":[65],"based":[66],"fusion":[67],"scheme":[68],"is":[69,109],"further":[70],"put":[71],"forward":[72],"learn":[74],"influence":[75],"degrees":[76],"dependence.":[82],"Experimental":[83],"results":[84],"show":[85],"that":[86],"performance":[89],"in":[90],"terms":[91],"root":[93],"mean":[94],"square":[95],"error":[96],"be":[98],"significantly":[99],"improved":[100],"compared":[101],"with":[102],"those":[103],"existing":[104],"algorithms.":[105],"The":[106],"accuracy":[108],"also":[110],"validated":[111],"by":[112],"using":[113],"sets":[116],"Telecom":[118],"Italia.":[119]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":41},{"year":2024,"cited_by_count":48},{"year":2023,"cited_by_count":41},{"year":2022,"cited_by_count":43},{"year":2021,"cited_by_count":46},{"year":2020,"cited_by_count":30},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":4}],"updated_date":"2026-07-14T08:27:34.040176","created_date":"2025-10-10T00:00:00"}
