{"id":"https://openalex.org/W3007592281","doi":"https://doi.org/10.1109/bigdata47090.2019.9006377","title":"Faulted Line Identification and Localization in Power System using Machine Learning Techniques","display_name":"Faulted Line Identification and Localization in Power System using Machine Learning Techniques","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3007592281","doi":"https://doi.org/10.1109/bigdata47090.2019.9006377","mag":"3007592281"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-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/A5010833275","display_name":"Ameema Zainab","orcid":"https://orcid.org/0000-0002-3754-4162"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ameema Zainab","raw_affiliation_strings":["Department of Electrical Engineering, Texas A&M University, College Station, Texas, U.S.A"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Texas A&M University, College Station, Texas, U.S.A","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031046256","display_name":"Shady S. Refaat","orcid":"https://orcid.org/0000-0001-9392-6141"},"institutions":[{"id":"https://openalex.org/I58152225","display_name":"Texas A&M University at Qatar","ror":"https://ror.org/03vb4dm14","country_code":"QA","type":"education","lineage":["https://openalex.org/I58152225","https://openalex.org/I91045830"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Shady S. Refaat","raw_affiliation_strings":["Department of Electrical Engineering, Texas A&M University at Qatar, Doha, Qatar"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Texas A&M University at Qatar, Doha, Qatar","institution_ids":["https://openalex.org/I58152225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086796838","display_name":"Dabeeruddin Syed","orcid":"https://orcid.org/0000-0002-9431-4849"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dabeeruddin Syed","raw_affiliation_strings":["Department of Electrical Engineering, Texas A&M University, College Station, Texas, U.S.A"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Texas A&M University, College Station, Texas, U.S.A","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014049864","display_name":"Ali Ghrayeb","orcid":"https://orcid.org/0000-0002-6808-5886"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ali Ghrayeb","raw_affiliation_strings":["Department of Electrical Engineering, Texas A&M University, College Station, Texas, U.S.A"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Texas A&M University, College Station, Texas, U.S.A","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010833171","display_name":"Haitham Abu\u2010Rub","orcid":"https://orcid.org/0000-0001-8687-3942"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haitham Abu-Rub","raw_affiliation_strings":["Department of Electrical Engineering, Texas A&M University, College Station, Texas, U.S.A"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Texas A&M University, College Station, Texas, U.S.A","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5010833275"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6632,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.84915307,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2975","last_page":"2981"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10972","display_name":"Power Systems Fault Detection","score":0.9998999834060669,"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/T10972","display_name":"Power Systems Fault Detection","score":0.9998999834060669,"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/T10305","display_name":"Power System Optimization and Stability","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T13183","display_name":"Islanding Detection in Power Systems","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/identification","display_name":"Identification (biology)","score":0.6870120763778687},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.6217548847198486},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6076847314834595},{"id":"https://openalex.org/keywords/electric-power-system","display_name":"Electric power system","score":0.47539031505584717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4243849515914917},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4129332900047302},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3450163006782532},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08351916074752808},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08310076594352722}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6870120763778687},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.6217548847198486},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6076847314834595},{"id":"https://openalex.org/C89227174","wikidata":"https://www.wikidata.org/wiki/Q2388981","display_name":"Electric power system","level":3,"score":0.47539031505584717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4243849515914917},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4129332900047302},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3450163006782532},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08351916074752808},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08310076594352722},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006377","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W255556494","https://openalex.org/W1654016072","https://openalex.org/W2336301173","https://openalex.org/W2466968898","https://openalex.org/W2520654854","https://openalex.org/W2773542761","https://openalex.org/W2790001494","https://openalex.org/W2791120310","https://openalex.org/W2791314150","https://openalex.org/W2800233816","https://openalex.org/W2884792776","https://openalex.org/W2905522942","https://openalex.org/W2906973030","https://openalex.org/W2915350869","https://openalex.org/W2942213799","https://openalex.org/W2972301508","https://openalex.org/W2981344804","https://openalex.org/W3145004415","https://openalex.org/W6746722929","https://openalex.org/W6757649157","https://openalex.org/W6767640441"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W3046775127","https://openalex.org/W4205958290","https://openalex.org/W3107474891","https://openalex.org/W3209574120","https://openalex.org/W3170094116"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,132],"data-driven":[4],"approach":[5,129],"has":[6],"been":[7,94,105],"used":[8],"to":[9,47,58,61,79,96,138],"identify":[10,50],"and":[11,49,70,87,102,151],"categorize":[12],"fault":[13,69,86,117],"in":[14],"the":[15,26,32,37,51,54,98,116,122,145,154,172],"electrical":[16],"power":[17],"system.":[18],"The":[19,39,107,127,148,164],"proposed":[20,95,108,128,155],"methodology":[21,109],"involves":[22],"efficient":[23],"analysis":[24],"of":[25,36,53,65,72,85,89,115,121,124,135,144,153,171],"data":[27,82],"with":[28,67,83,131],"feature":[29],"vectors":[30],"including":[31],"area":[33],"or":[34],"zone":[35],"bus.":[38],"training":[40],"is":[41,175],"done":[42],"on":[43,159,169],"machine":[44],"learning":[45],"models":[46],"classify":[48],"location":[52,88],"fault.":[55,90],"Three-phase,":[56],"line":[57,66],"ground,":[59,62],"line-to-line":[60],"line-to-line,":[63],"loss":[64,71],"no":[68],"load":[73],"at":[74],"bus":[75,162],"faults":[76],"are":[77,157],"simulated":[78],"generate":[80],"labeled":[81],"type":[84],"Two":[91],"algorithms":[92],"have":[93,104],"choose":[97],"measurements":[99],"selection":[100],"strategy,":[101],"results":[103],"stated.":[106],"proves":[110],"its":[111],"validity":[112],"for":[113],"identification":[114],"without":[118],"necessary":[119],"measurement":[120],"voltage":[123],"each":[125],"node.":[126],"works":[130],"minimum":[133],"number":[134],"buses":[136],"required":[137],"be":[139],"as":[140,142],"few":[141],"5-7%":[143],"measured":[146],"buses.":[147],"accuracy,":[149],"capabilities,":[150],"limitations":[152],"algorithm":[156],"verified":[158],"IEEE":[160],"68":[161],"model.":[163],"highest":[165],"classification":[166],"accuracy":[167],"attained":[168],"one":[170],"test":[173],"cases":[174],"91%.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
