{"id":"https://openalex.org/W4383113422","doi":"https://doi.org/10.1109/jsyst.2023.3287413","title":"A Global Cyber-Resilient Model for Dynamic Line Rating Forecasting Based on Deep Federated Learning","display_name":"A Global Cyber-Resilient Model for Dynamic Line Rating Forecasting Based on Deep Federated Learning","publication_year":2023,"publication_date":"2023-07-04","ids":{"openalex":"https://openalex.org/W4383113422","doi":"https://doi.org/10.1109/jsyst.2023.3287413"},"language":"en","primary_location":{"id":"doi:10.1109/jsyst.2023.3287413","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/jsyst.2023.3287413","pdf_url":null,"source":{"id":"https://openalex.org/S95999327","display_name":"IEEE Systems Journal","issn_l":"1932-8184","issn":["1932-8184","1937-9234","2373-7816"],"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 Systems Journal","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.1109/JSYST.2023.3287413","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042769539","display_name":"Hamed Moayyed","orcid":"https://orcid.org/0000-0001-7075-1609"},"institutions":[{"id":"https://openalex.org/I83863532","display_name":"Polytechnic Institute of Porto","ror":"https://ror.org/04988re48","country_code":"PT","type":"education","lineage":["https://openalex.org/I83863532"]}],"countries":["PT"],"is_corresponding":true,"raw_author_name":"Hamed Moayyed","raw_affiliation_strings":["GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Porto, Portugal","Polytechnic of Porto, Porto, Portugal"],"affiliations":[{"raw_affiliation_string":"GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Porto, Portugal","institution_ids":[]},{"raw_affiliation_string":"Polytechnic of Porto, Porto, Portugal","institution_ids":["https://openalex.org/I83863532"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051164485","display_name":"Arash Moradzadeh","orcid":"https://orcid.org/0000-0002-2557-1307"},"institutions":[{"id":"https://openalex.org/I41832843","display_name":"University of Tabriz","ror":"https://ror.org/01papkj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I41832843"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Arash Moradzadeh","raw_affiliation_strings":["Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran","institution_ids":["https://openalex.org/I41832843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068581805","display_name":"Amin Mansour\u2010Saatloo","orcid":"https://orcid.org/0000-0002-7230-7648"},"institutions":[{"id":"https://openalex.org/I41832843","display_name":"University of Tabriz","ror":"https://ror.org/01papkj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I41832843"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Amin Mansour-Saatloo","raw_affiliation_strings":["Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran","institution_ids":["https://openalex.org/I41832843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016541935","display_name":"Behnam Mohammadi\u2010Ivatloo","orcid":"https://orcid.org/0000-0002-0255-8353"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]},{"id":"https://openalex.org/I41832843","display_name":"University of Tabriz","ror":"https://ror.org/01papkj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I41832843"]}],"countries":["DK","IR"],"is_corresponding":false,"raw_author_name":"Behnam Mohammadi-Ivatloo","raw_affiliation_strings":["Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran","Department of Energy Technology, Aalborg University, Aalborg, Denmark"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran","institution_ids":["https://openalex.org/I41832843"]},{"raw_affiliation_string":"Department of Energy Technology, Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064698212","display_name":"Mehdi Abapour","orcid":"https://orcid.org/0000-0003-0241-7021"},"institutions":[{"id":"https://openalex.org/I41832843","display_name":"University of Tabriz","ror":"https://ror.org/01papkj44","country_code":"IR","type":"education","lineage":["https://openalex.org/I41832843"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mehdi Abapour","raw_affiliation_strings":["Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran"],"affiliations":[{"raw_affiliation_string":"Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran","institution_ids":["https://openalex.org/I41832843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089283900","display_name":"Zita Vale","orcid":"https://orcid.org/0000-0002-4560-9544"},"institutions":[{"id":"https://openalex.org/I83863532","display_name":"Polytechnic Institute of Porto","ror":"https://ror.org/04988re48","country_code":"PT","type":"education","lineage":["https://openalex.org/I83863532"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Zita Vale","raw_affiliation_strings":["GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Porto, Portugal","Polytechnic of Porto, Porto, Portugal"],"affiliations":[{"raw_affiliation_string":"GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, Porto, Portugal","institution_ids":[]},{"raw_affiliation_string":"Polytechnic of Porto, Porto, Portugal","institution_ids":["https://openalex.org/I83863532"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5042769539"],"corresponding_institution_ids":["https://openalex.org/I83863532"],"apc_list":null,"apc_paid":null,"fwci":1.1256,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77499538,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"17","issue":"4","first_page":"6390","last_page":"6400"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12804","display_name":"Thermal Analysis in Power Transmission","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T12804","display_name":"Thermal Analysis in Power Transmission","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T10972","display_name":"Power Systems Fault Detection","score":0.9961000084877014,"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":0.7333984971046448},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.7088159918785095},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.7044292688369751},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5507135391235352},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5443730354309082},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49887919425964355},{"id":"https://openalex.org/keywords/smart-grid","display_name":"Smart grid","score":0.4704688489437103},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46520382165908813},{"id":"https://openalex.org/keywords/renewable-energy","display_name":"Renewable energy","score":0.4449293315410614},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.44289931654930115},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42902472615242004},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42750316858291626},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.4249488413333893},{"id":"https://openalex.org/keywords/overhead-line","display_name":"Overhead line","score":0.4150146245956421},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.333767831325531},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12365290522575378}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7333984971046448},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.7088159918785095},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.7044292688369751},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5507135391235352},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5443730354309082},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49887919425964355},{"id":"https://openalex.org/C10558101","wikidata":"https://www.wikidata.org/wiki/Q689855","display_name":"Smart grid","level":2,"score":0.4704688489437103},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46520382165908813},{"id":"https://openalex.org/C188573790","wikidata":"https://www.wikidata.org/wiki/Q12705","display_name":"Renewable energy","level":2,"score":0.4449293315410614},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44289931654930115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42902472615242004},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42750316858291626},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.4249488413333893},{"id":"https://openalex.org/C2775861652","wikidata":"https://www.wikidata.org/wiki/Q110701","display_name":"Overhead line","level":2,"score":0.4150146245956421},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.333767831325531},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12365290522575378},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/jsyst.2023.3287413","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/jsyst.2023.3287413","pdf_url":null,"source":{"id":"https://openalex.org/S95999327","display_name":"IEEE Systems Journal","issn_l":"1932-8184","issn":["1932-8184","1937-9234","2373-7816"],"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 Systems Journal","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/7cc48ebf-a545-40ab-bd6a-fcaa6792bbc6","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/7cc48ebf-a545-40ab-bd6a-fcaa6792bbc6","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Moayyed, H, Moradzadeh, A, Mansour-Saatloo, A, Abapour, M, Abapour, M & Vale, Z 2023, 'A Global Cyber-Resilient Model for Dynamic Line Rating Forecasting Based on Deep Federated Learning', IEEE Systems Journal, vol. 17, no. 4, pp. 6390-6400. https://doi.org/10.1109/JSYST.2023.3287413","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:zenodo.org:8386926","is_oa":true,"landing_page_url":"https://doi.org/10.1109/JSYST.2023.3287413","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"IEEE Systems Journal, 1-11, (2023-09-28)","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:8386926","is_oa":true,"landing_page_url":"https://doi.org/10.1109/JSYST.2023.3287413","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"IEEE Systems Journal, 1-11, (2023-09-28)","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335322","display_name":"European Regional Development Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2016040684","https://openalex.org/W2282689981","https://openalex.org/W2319367234","https://openalex.org/W2580788515","https://openalex.org/W2776165575","https://openalex.org/W2789258636","https://openalex.org/W2797597296","https://openalex.org/W2884807580","https://openalex.org/W2921757941","https://openalex.org/W2922709255","https://openalex.org/W2934137331","https://openalex.org/W2953453671","https://openalex.org/W2964105969","https://openalex.org/W2964782836","https://openalex.org/W2979841552","https://openalex.org/W2979847038","https://openalex.org/W2998393088","https://openalex.org/W3045836002","https://openalex.org/W3047715801","https://openalex.org/W3081576544","https://openalex.org/W3121442875","https://openalex.org/W3128628857","https://openalex.org/W3133402591","https://openalex.org/W3136186822","https://openalex.org/W3195600610","https://openalex.org/W3215609696","https://openalex.org/W4205160218","https://openalex.org/W4225007045","https://openalex.org/W4248453363","https://openalex.org/W4283593412","https://openalex.org/W4318619660","https://openalex.org/W6728757088"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W2863145157","https://openalex.org/W2899420506","https://openalex.org/W4399743551","https://openalex.org/W3112039675","https://openalex.org/W2045043427","https://openalex.org/W3111604547"],"abstract_inverted_index":{"Uncertainty":[0],"in":[1,30,142],"renewable":[2],"energy":[3,6],"generation":[4,9],"and":[5,22,95,132,139,182,192,202,246,254],"demand":[7,23],"reduces":[8],"flexibility,":[10],"which":[11,31,204],"should":[12],"be":[13],"compensated":[14],"by":[15],"increasing":[16],"flexibility":[17],"on":[18,120,150,159,208],"the":[19,32,71,76,80,107,113,160,166,177,186,209,212,217,230,241],"supply":[20],"grid":[21],"sides.":[24],"Dynamic":[25],"line":[26],"rating":[27],"(DLR)":[28],"forecasting,":[29],"maximum":[33],"current":[34],"carrying":[35],"capacity":[36],"of":[37,101,106,126,137,211,216,243,251],"overhead":[38],"transmission":[39],"lines":[40],"is":[41,44,117,148,173,188,234],"accurately":[42,74],"forecasted,":[43],"important":[45],"to":[46,175,236],"enable":[47],"secure":[48],"grid-side":[49],"flexibility.":[50],"This":[51],"article":[52],"introduces":[53],"a":[54,61,68,170],"novel":[55],"model":[56],"for":[57,82,180,240],"DLR":[58,77,178,238],"forecasting":[59],"using":[60,154,190,221],"federated":[62,115,167],"learning":[63,156],"(FL)":[64],"approach.":[65],"By":[66],"generating":[67],"global":[69,232],"model,":[70],"FL":[72,108,147],"can":[73],"forecast":[75,176,237],"values":[78,179,239],"without":[79],"need":[81],"data":[83,92,96,121,194],"from":[84,98,122,146,163,195],"regions":[85,125,242],"that":[86,128,172,229],"are":[87,103,219],"not":[88],"available.":[89],"In":[90,110],"addition,":[91],"security":[93],"protection":[94,97],"various":[99,222],"types":[100],"cyberattacks":[102],"prominent":[104],"features":[105,161],"technique.":[109],"this":[111],"article,":[112],"proposed":[114],"network":[116,168],"trained":[118],"based":[119,149],"nine":[123],"different":[124,130],"Iran":[127],"have":[129],"geographical":[131,191],"meteorological":[133,193],"features.":[134],"The":[135,214,226],"process":[136],"training":[138],"recognizing":[140],"patterns":[141],"each":[143,164],"local":[144],"client":[145],"convolutional":[151],"neural":[152],"networks":[153],"deep":[155],"techniques.":[157],"Based":[158],"extracted":[162],"client,":[165],"generates":[169],"supermodel":[171,187,233],"able":[174,235],"new":[181,197],"unknown":[183],"regions.":[184],"Generating":[185],"performed":[189],"three":[196],"regions,":[198],"namely":[199],"Boroujen,":[200,244],"Nahavand,":[201,245],"Rafsanjan,":[203,247],"had":[205],"no":[206],"effect":[207],"construction":[210],"supermodel.":[213],"results":[215],"forecasts":[218],"analyzed":[220],"performance":[223],"evaluation":[224],"metrics.":[225],"evaluations":[227],"show":[228],"generated":[231],"with":[248],"correlation":[249],"coefficients":[250],"96%,":[252],"94%,":[253],"97%,":[255],"respectively.":[256]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}