{"id":"https://openalex.org/W3162224075","doi":"https://doi.org/10.1109/lwc.2021.3078745","title":"Time-Wise Attention Aided Convolutional Neural Network for Data-Driven Cellular Traffic Prediction","display_name":"Time-Wise Attention Aided Convolutional Neural Network for Data-Driven Cellular Traffic Prediction","publication_year":2021,"publication_date":"2021-05-10","ids":{"openalex":"https://openalex.org/W3162224075","doi":"https://doi.org/10.1109/lwc.2021.3078745","mag":"3162224075"},"language":"en","primary_location":{"id":"doi:10.1109/lwc.2021.3078745","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2021.3078745","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Wireless 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/A5110661845","display_name":"Wenxin Shen","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":true,"raw_author_name":"Wenxin Shen","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China","Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]},{"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":["School of Control Science and Engineering, Shandong University, Jinan, China","Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]},{"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/A5043457090","display_name":"Shuaishuai Guo","orcid":"https://orcid.org/0000-0003-0885-7327"},"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":"Shuaishuai Guo","raw_affiliation_strings":["School of Control Science and Engineering, Shandong University, Jinan, China","Shandong Provincial Key Laboratory of Wireless Communication Technologies, Shandong University, Jinan, China"],"affiliations":[{"raw_affiliation_string":"School of Control Science and Engineering, Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]},{"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/A5045797640","display_name":"Chuanting Zhang","orcid":"https://orcid.org/0000-0002-6685-4071"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Chuanting Zhang","raw_affiliation_strings":["Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Computer, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Computer, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5110661845"],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":4.6264,"has_fulltext":false,"cited_by_count":53,"citation_normalized_percentile":{"value":0.95242728,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"10","issue":"8","first_page":"1747","last_page":"1751"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9945999979972839,"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/T10524","display_name":"Traffic control and management","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/computer-science","display_name":"Computer science","score":0.8351770639419556},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7224981188774109},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.6270430684089661},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.559891939163208},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.5296145677566528},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5202678442001343},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49630504846572876},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4729958474636078},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4497883915901184},{"id":"https://openalex.org/keywords/cellular-traffic","display_name":"Cellular traffic","score":0.4418289363384247},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43366968631744385},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4173800051212311},{"id":"https://openalex.org/keywords/cellular-network","display_name":"Cellular network","score":0.4102056622505188},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3706568777561188},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07439348101615906}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8351770639419556},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7224981188774109},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.6270430684089661},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.559891939163208},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.5296145677566528},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5202678442001343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49630504846572876},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4729958474636078},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4497883915901184},{"id":"https://openalex.org/C133972139","wikidata":"https://www.wikidata.org/wiki/Q5058371","display_name":"Cellular traffic","level":3,"score":0.4418289363384247},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43366968631744385},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4173800051212311},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.4102056622505188},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3706568777561188},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07439348101615906},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"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/lwc.2021.3078745","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lwc.2021.3078745","pdf_url":null,"source":{"id":"https://openalex.org/S2500830676","display_name":"IEEE Wireless Communications Letters","issn_l":"2162-2337","issn":["2162-2337","2162-2345"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Wireless Communications Letters","raw_type":"journal-article"},{"id":"pmh:oai:repository.kaust.edu.sa:10754/669230","is_oa":false,"landing_page_url":"http://hdl.handle.net/10754/669230","pdf_url":null,"source":{"id":"https://openalex.org/S4306401596","display_name":"King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I71920554","host_organization_name":"King Abdullah University of Science and Technology","host_organization_lineage":["https://openalex.org/I71920554"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G96062130","display_name":null,"funder_award_id":"61860206005","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/W295894637","https://openalex.org/W1522301498","https://openalex.org/W1991898587","https://openalex.org/W2052024782","https://openalex.org/W2190432600","https://openalex.org/W2789386460","https://openalex.org/W2807536558","https://openalex.org/W2921319277","https://openalex.org/W2963403868","https://openalex.org/W2964121744","https://openalex.org/W3010459612","https://openalex.org/W3034215963","https://openalex.org/W3038397330","https://openalex.org/W3084521418","https://openalex.org/W3108866920","https://openalex.org/W4385245566","https://openalex.org/W6687472758","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W2039858536","https://openalex.org/W2740787378","https://openalex.org/W2152560098","https://openalex.org/W2276501992","https://openalex.org/W2774283532","https://openalex.org/W4320801776","https://openalex.org/W2942897781","https://openalex.org/W1564218952","https://openalex.org/W2538283180","https://openalex.org/W2001116016"],"abstract_inverted_index":{"Recurrent":[0],"neural":[1,72,103],"network":[2,73,104],"(RNN)":[3],"based":[4],"models":[5],"are":[6],"widely":[7],"adopted":[8,89,107],"to":[9,90,108],"capture":[10,45,51,91,109],"temporal":[11,30,47,54,93],"dependencies":[12,31,94],"in":[13,44,61,117,122,141],"the":[14,46,52,58,81,84,96,101,110],"state-of-the-art":[15],"approaches":[16],"for":[17,76],"cellular":[18,77,97,124],"traffic":[19,33,62,78,98,118,125],"prediction.":[20,79],"However,":[21],"RNN":[22],"is":[23,88,106,120],"inefficient":[24],"and":[25,56,100,149],"incapable":[26],"of":[27,32,95,115,143],"capturing":[28],"long-range":[29,92],"data.":[34],"Besides,":[35],"its":[36],"inherent":[37],"sequential":[38],"nature":[39],"makes":[40],"it":[41],"time":[42,60],"consuming":[43],"dependencies.":[48],"To":[49],"better":[50],"long-term":[53],"dependency":[55],"reduce":[57],"consumed":[59],"data":[63,99],"prediction,":[64],"we":[65],"propose":[66],"a":[67],"time-wise":[68,85],"attention":[69,86],"aided":[70],"convolutional":[71,102],"(TWACNet)":[74],"structure":[75],"In":[80],"proposed":[82,132],"TWACNet,":[83],"mechanism":[87],"(CNN)":[105],"spatial":[111],"correlation.":[112],"The":[113],"performance":[114],"TWACNet":[116],"prediction":[119,139],"tested":[121],"real-world":[123],"datasets.":[126],"Experimental":[127],"results":[128],"demonstrate":[129],"that":[130],"our":[131],"approach":[133],"can":[134],"considerably":[135],"outperform":[136],"those":[137],"existing":[138],"methods":[140],"terms":[142],"root":[144],"mean":[145],"square":[146],"errors":[147],"(RMSE)":[148],"training":[150],"time.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}