{"id":"https://openalex.org/W3138697184","doi":"https://doi.org/10.1109/access.2021.3068610","title":"Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System","display_name":"Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3138697184","doi":"https://doi.org/10.1109/access.2021.3068610","mag":"3138697184"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3068610","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3068610","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09385061.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09385061.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113977841","display_name":"Nadia Adnan Shiltagh Al\u2010Jamali","orcid":null},"institutions":[{"id":"https://openalex.org/I135120706","display_name":"University of Baghdad","ror":"https://ror.org/007f1da21","country_code":"IQ","type":"education","lineage":["https://openalex.org/I135120706"]},{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB","IQ"],"is_corresponding":false,"raw_author_name":"Nadia Adnan Shiltagh Al-Jamali","raw_affiliation_strings":["Department of Computer Engineering, University of Baghdad, Baghdad, Iraq","Department of Electrical and Computer Engineering, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, U.K"],"raw_orcid":"https://orcid.org/0000-0002-0377-1519","affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, University of Baghdad, Baghdad, Iraq","institution_ids":["https://openalex.org/I135120706"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, U.K","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036588740","display_name":"Hamed Al\u2010Raweshidy","orcid":"https://orcid.org/0000-0002-3702-8192"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hamed S. Al-Raweshidy","raw_affiliation_strings":["Department of Electrical and Computer Engineering, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, U.K"],"raw_orcid":"https://orcid.org/0000-0002-3702-8192","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, U.K","institution_ids":["https://openalex.org/I59433898"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":11.1435,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.97887434,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"47864","last_page":"47874"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9865000247955322,"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/T12676","display_name":"Machine Learning and ELM","score":0.9848999977111816,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8054583072662354},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6596925258636475},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6124968528747559},{"id":"https://openalex.org/keywords/network-congestion","display_name":"Network congestion","score":0.5631536841392517},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5604401230812073},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5366643667221069},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4897792339324951},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.4537303149700165},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.4416579604148865},{"id":"https://openalex.org/keywords/network-traffic-control","display_name":"Network traffic control","score":0.4251987040042877},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.41195639967918396},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.3512724041938782},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3423638939857483},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14132827520370483},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.0899430513381958}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8054583072662354},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6596925258636475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6124968528747559},{"id":"https://openalex.org/C195563490","wikidata":"https://www.wikidata.org/wiki/Q180368","display_name":"Network congestion","level":3,"score":0.5631536841392517},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5604401230812073},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5366643667221069},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4897792339324951},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.4537303149700165},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.4416579604148865},{"id":"https://openalex.org/C201100257","wikidata":"https://www.wikidata.org/wiki/Q393287","display_name":"Network traffic control","level":3,"score":0.4251987040042877},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.41195639967918396},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.3512724041938782},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3423638939857483},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14132827520370483},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0899430513381958},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2021.3068610","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3068610","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09385061.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:bura.brunel.ac.uk:2438/22890","is_oa":true,"landing_page_url":"https://bura.brunel.ac.uk/handle/2438/22890","pdf_url":null,"source":{"id":"https://openalex.org/S4306401473","display_name":"Brunel University Research Archive (BURA) (Brunel University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I59433898","host_organization_name":"Brunel University of London","host_organization_lineage":["https://openalex.org/I59433898"],"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":"","raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:850105a2cd3149d4a9e09145ce799478","is_oa":true,"landing_page_url":"https://doaj.org/article/850105a2cd3149d4a9e09145ce799478","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":"IEEE Access, Vol 9, Pp 47864-47874 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3068610","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3068610","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09385061.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3138697184.pdf","grobid_xml":"https://content.openalex.org/works/W3138697184.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W2558572149","https://openalex.org/W2792827505","https://openalex.org/W2794573138","https://openalex.org/W2804686008","https://openalex.org/W2895544118","https://openalex.org/W2905149963","https://openalex.org/W2908993293","https://openalex.org/W2915969651","https://openalex.org/W2917463589","https://openalex.org/W2920358140","https://openalex.org/W2946228438","https://openalex.org/W2966732743","https://openalex.org/W2968773512","https://openalex.org/W2969906462","https://openalex.org/W2970476308","https://openalex.org/W2971710819","https://openalex.org/W2974401122","https://openalex.org/W2995544081","https://openalex.org/W2995819689","https://openalex.org/W2997058333","https://openalex.org/W2999146029","https://openalex.org/W2999561085","https://openalex.org/W3000748319","https://openalex.org/W3003368676","https://openalex.org/W3003534552","https://openalex.org/W3003689553","https://openalex.org/W3004568231","https://openalex.org/W3004889728","https://openalex.org/W3005096593","https://openalex.org/W3006247566","https://openalex.org/W3008641316","https://openalex.org/W3008725350","https://openalex.org/W3010683536","https://openalex.org/W3010924788","https://openalex.org/W3018115347","https://openalex.org/W3046105738","https://openalex.org/W3098133185","https://openalex.org/W3102127038","https://openalex.org/W3105000568","https://openalex.org/W4230237401","https://openalex.org/W6749292879"],"related_works":["https://openalex.org/W2374774854","https://openalex.org/W2347295639","https://openalex.org/W2147074439","https://openalex.org/W2560201450","https://openalex.org/W1990799529","https://openalex.org/W1985457510","https://openalex.org/W2744383474","https://openalex.org/W4382053425","https://openalex.org/W3038296958","https://openalex.org/W2372056697"],"abstract_inverted_index":{"An":[0],"Intelligent":[1,10,42],"Internet":[2,43],"of":[3,44,65,144,200,202],"Things":[4,45],"network":[5,46,204,210],"based":[6,47,114],"on":[7,48,115],"an":[8,26,41],"Artificial":[9],"System,":[11],"can":[12],"substantially":[13],"control":[14],"and":[15,92,105],"reduce":[16],"the":[17,21,34,66,94,97,129,133,138,142,156,161,173,198,203,209],"congestion":[18,35],"effects":[19,36],"in":[20,37,40,136],"network.":[22,95],"In":[23,96],"this":[24],"paper,":[25],"artificial":[27,81,157],"intelligent":[28,82,158],"system":[29,83,159],"is":[30,84,103,152,178,205,212],"proposed":[31,98,153],"for":[32,86,207],"eliminating":[33],"traffic":[38,90],"load":[39],"a":[49,57,116,191],"deep":[50,117,147],"learning":[51,118,148],"Convolutional":[52],"Recurrent":[53,194,221],"Neural":[54,195,222],"Network":[55],"with":[56,111,190,218],"modified":[58,67,119,124,149,184],"Element-wise":[59,68,120,125,185],"Attention":[60,69,121,126,186],"Gate.":[61,122],"The":[62,80,123,168],"invisible":[63],"layer":[64],"Gate":[70,127,187],"structure":[71],"has":[72,128],"self-feedback":[73],"to":[74,107,131,154,163],"increase":[75],"its":[76,109],"long":[77],"short-term":[78],"memory.":[79],"implemented":[85],"next":[87],"step":[88],"ahead":[89],"estimation":[91],"clustering":[93],"architecture,":[99],"each":[100],"sensing":[101],"node":[102],"adaptive":[104],"able":[106],"change":[108],"affiliation":[110],"other":[112],"clusters":[113],"ability":[130],"handle":[132],"buffer":[134],"capacity":[135],"all":[137],"network,":[139],"thereby":[140],"enriching":[141],"Quality":[143,199],"Service.":[145],"A":[146],"training":[150],"algorithm":[151],"learn":[155],"allowing":[160],"neurons":[162],"have":[164],"greater":[165],"concentration":[166],"ability.":[167],"simulation":[169],"results":[170],"demonstrate":[171],"that":[172],"Root":[174],"Mean":[175],"Square":[176],"error":[177],"minimized":[179],"by":[180,214],"37.14%":[181],"when":[182,188],"using":[183],"compared":[189],"Deep":[192,219],"Learning":[193,220],"Network.":[196,223],"Also,":[197],"Service":[201],"improved,":[206],"example,":[208],"lifetime":[211],"enhanced":[213],"12.7%":[215],"more":[216],"than":[217]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}