{"id":"https://openalex.org/W3031952083","doi":"https://doi.org/10.4018/ijitn.2020070103","title":"Congestion Prediction System With Artificial Neural Networks","display_name":"Congestion Prediction System With Artificial Neural Networks","publication_year":2020,"publication_date":"2020-05-28","ids":{"openalex":"https://openalex.org/W3031952083","doi":"https://doi.org/10.4018/ijitn.2020070103","mag":"3031952083"},"language":"en","primary_location":{"id":"doi:10.4018/ijitn.2020070103","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijitn.2020070103","pdf_url":null,"source":{"id":"https://openalex.org/S32289611","display_name":"International Journal of Interdisciplinary Telecommunications and Networking","issn_l":"1941-8663","issn":["1941-8663","1941-8671"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Interdisciplinary Telecommunications and Networking","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/A5034017133","display_name":"Fatma G\u00fcm\u00fc\u015f","orcid":"https://orcid.org/0000-0001-5191-0037"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Fatma Gumus","raw_affiliation_strings":["Yildiz Technical University, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yildiz Technical University, Turkey","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082950744","display_name":"Derya Yiltas-Kaplan","orcid":"https://orcid.org/0000-0001-8370-8941"},"institutions":[{"id":"https://openalex.org/I4210112471","display_name":"Istanbul University-Cerrahpa\u015fa","ror":"https://ror.org/01dzn5f42","country_code":"TR","type":"education","lineage":["https://openalex.org/I4210112471"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Derya Yiltas-Kaplan","raw_affiliation_strings":["\u0130stanbul University-Cerrahpa\u015fa, Turkey"],"raw_orcid":"https://orcid.org/0000-0001-8370-8941","affiliations":[{"raw_affiliation_string":"\u0130stanbul University-Cerrahpa\u015fa, Turkey","institution_ids":["https://openalex.org/I4210112471"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1621,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52170168,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"12","issue":"3","first_page":"28","last_page":"43"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10714","display_name":"Software-Defined Networks and 5G","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10714","display_name":"Software-Defined Networks and 5G","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9940999746322632,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8566786050796509},{"id":"https://openalex.org/keywords/nonlinear-autoregressive-exogenous-model","display_name":"Nonlinear autoregressive exogenous model","score":0.7578314542770386},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7308822870254517},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6063502430915833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5874337553977966},{"id":"https://openalex.org/keywords/network-congestion","display_name":"Network congestion","score":0.5492891073226929},{"id":"https://openalex.org/keywords/probabilistic-neural-network","display_name":"Probabilistic neural network","score":0.543882429599762},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.5236468315124512},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4968302547931671},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.4669764041900635},{"id":"https://openalex.org/keywords/time-delay-neural-network","display_name":"Time delay neural network","score":0.44552081823349},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.41323041915893555},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.41075029969215393},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35875070095062256},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.12331664562225342}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8566786050796509},{"id":"https://openalex.org/C42536954","wikidata":"https://www.wikidata.org/wiki/Q7049462","display_name":"Nonlinear autoregressive exogenous model","level":3,"score":0.7578314542770386},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7308822870254517},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6063502430915833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5874337553977966},{"id":"https://openalex.org/C195563490","wikidata":"https://www.wikidata.org/wiki/Q180368","display_name":"Network congestion","level":3,"score":0.5492891073226929},{"id":"https://openalex.org/C134342201","wikidata":"https://www.wikidata.org/wiki/Q7246859","display_name":"Probabilistic neural network","level":4,"score":0.543882429599762},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.5236468315124512},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4968302547931671},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.4669764041900635},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.44552081823349},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.41323041915893555},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.41075029969215393},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35875070095062256},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.12331664562225342},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/ijitn.2020070103","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijitn.2020070103","pdf_url":null,"source":{"id":"https://openalex.org/S32289611","display_name":"International Journal of Interdisciplinary Telecommunications and Networking","issn_l":"1941-8663","issn":["1941-8663","1941-8671"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Interdisciplinary Telecommunications and Networking","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jitn00:v:12:y:2020:i:3:p:28-43","is_oa":false,"landing_page_url":"https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJITN.2020070103","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1707144927","https://openalex.org/W1840338487","https://openalex.org/W1904365287","https://openalex.org/W1971703394","https://openalex.org/W1994926493","https://openalex.org/W2028312366","https://openalex.org/W2040978774","https://openalex.org/W2042522292","https://openalex.org/W2057141851","https://openalex.org/W2058956791","https://openalex.org/W2087070363","https://openalex.org/W2110722699","https://openalex.org/W2145091572","https://openalex.org/W2147524058","https://openalex.org/W2150093579","https://openalex.org/W2154053567","https://openalex.org/W2156571267","https://openalex.org/W2158051955","https://openalex.org/W2159065703","https://openalex.org/W2163742780","https://openalex.org/W2236623899","https://openalex.org/W2475596014","https://openalex.org/W2488544472","https://openalex.org/W2562498401","https://openalex.org/W4211055425","https://openalex.org/W4254218124","https://openalex.org/W6637473994","https://openalex.org/W6826519151"],"related_works":["https://openalex.org/W1595652908","https://openalex.org/W2089093251","https://openalex.org/W2950022897","https://openalex.org/W3177279640","https://openalex.org/W2104714048","https://openalex.org/W2390775476","https://openalex.org/W2950917560","https://openalex.org/W2186233897","https://openalex.org/W2785001934","https://openalex.org/W2408618716"],"abstract_inverted_index":{"Software":[0],"Defined":[1],"Network":[2,98,108],"(SDN)":[3],"is":[4,22],"a":[5,33],"programmable":[6],"network":[7],"architecture":[8],"that":[9,132],"provides":[10],"innovative":[11],"solutions":[12],"to":[13,122,147],"the":[14,17,55,59,69,81,91,123,126,135],"problems":[15],"of":[16,64,71,125],"traditional":[18],"networks.":[19,43],"Congestion":[20],"control":[21],"still":[23],"an":[24,74],"uncharted":[25],"territory":[26],"for":[27],"this":[28,31,65],"technology.":[29],"In":[30],"work,":[32],"congestion":[34,76],"prediction":[35,77,137],"scheme":[36],"has":[37],"been":[38,116],"developed":[39],"by":[40],"using":[41],"neural":[42],"Minimum":[44],"Redundancy":[45],"Maximum":[46],"Relevance":[47],"(mRMR)":[48],"feature":[49],"selection":[50],"algorithm":[51],"was":[52,134],"performed":[53],"on":[54],"data":[56],"collected":[57],"from":[58],"OMNET++":[60],"simulation.":[61],"The":[62,129],"novelty":[63],"study":[66],"also":[67],"covers":[68],"implementation":[70],"mRMR":[72],"in":[73,119],"SDN":[75],"problem.":[78],"After":[79],"evaluating":[80],"relevance":[82],"scores,":[83],"two":[84],"highest":[85],"ranking":[86],"features":[87],"were":[88,110],"used.":[89],"On":[90],"learning":[92,141],"stage":[93],"Nonlinear":[94,100,105],"Autoregressive":[95,101],"Exogenous":[96],"Neural":[97,102,107],"(NARX),":[99],"Network,":[103],"and":[104,150],"Feedforward":[106],"algorithms":[109,113],"executed.":[111],"These":[112],"had":[114],"not":[115],"used":[117],"before":[118],"SDNs":[120],"according":[121],"best":[124,136],"authors":[127],"knowledge.":[128],"experiments":[130],"represented":[131],"NARX":[133],"algorithm.":[138],"This":[139],"machine":[140],"approach":[142],"can":[143],"be":[144],"easily":[145],"integrated":[146],"different":[148],"topologies":[149],"application":[151],"areas.":[152]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
