{"id":"https://openalex.org/W7101388692","doi":"https://doi.org/10.34133/icomputing.0229","title":"Evolutionary Graph Neural Architecture Search with Mask Predictor for Power Distribution Network Fault Detection","display_name":"Evolutionary Graph Neural Architecture Search with Mask Predictor for Power Distribution Network Fault Detection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7101388692","doi":"https://doi.org/10.34133/icomputing.0229"},"language":"en","primary_location":{"id":"doi:10.34133/icomputing.0229","is_oa":true,"landing_page_url":"https://doi.org/10.34133/icomputing.0229","pdf_url":null,"source":{"id":"https://openalex.org/S4387281904","display_name":"Intelligent Computing","issn_l":"2771-5892","issn":["2771-5892"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.34133/icomputing.0229","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Wenjie Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I4387152397","display_name":"State Grid Hebei Electric Power Company","ror":"https://ror.org/02v4yxp84","country_code":null,"type":"company","lineage":["https://openalex.org/I4387152397"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Wenjie Fu","raw_affiliation_strings":["State Grid Hebei Electric Power Company"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Hebei Electric Power Company","institution_ids":["https://openalex.org/I4387152397"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I4387152397","display_name":"State Grid Hebei Electric Power Company","ror":"https://ror.org/02v4yxp84","country_code":null,"type":"company","lineage":["https://openalex.org/I4387152397"]}],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Cui","raw_affiliation_strings":["State Grid Hebei Electric Power Company"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Hebei Electric Power Company","institution_ids":["https://openalex.org/I4387152397"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shuai Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]},{"id":"https://openalex.org/I4210126065","display_name":"Shanghai Electric (China)","ror":"https://ror.org/0314qy595","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210126065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Zhang","raw_affiliation_strings":["Hengshui Branch, State Grid Hebei Electric Power Company"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hengshui Branch, State Grid Hebei Electric Power Company","institution_ids":["https://openalex.org/I17442442","https://openalex.org/I4210126065"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhipeng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164033","display_name":"Smart Metering Systems (United Kingdom)","ror":"https://ror.org/05gn43523","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210164033"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhipeng Li","raw_affiliation_strings":["Henan XJ Metering Co. Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan XJ Metering Co. Ltd","institution_ids":["https://openalex.org/I4210164033"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lei Chen","orcid":"https://orcid.org/0009-0008-6953-228X"},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]},{"id":"https://openalex.org/I4210126065","display_name":"Shanghai Electric (China)","ror":"https://ror.org/0314qy595","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210126065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["Hengshui Branch, State Grid Hebei Electric Power Company"],"raw_orcid":"https://orcid.org/0009-0008-6953-228X","affiliations":[{"raw_affiliation_string":"Hengshui Branch, State Grid Hebei Electric Power Company","institution_ids":["https://openalex.org/I17442442","https://openalex.org/I4210126065"]}]},{"author_position":"last","author":{"id":null,"display_name":"Peng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210164033","display_name":"Smart Metering Systems (United Kingdom)","ror":"https://ror.org/05gn43523","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210164033"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Peng Li","raw_affiliation_strings":["Henan XJ Metering Co. Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Henan XJ Metering Co. Ltd","institution_ids":["https://openalex.org/I4210164033"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.48939499,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10972","display_name":"Power Systems Fault Detection","score":0.3513999879360199,"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":0.3513999879360199,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.15729999542236328,"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"}},{"id":"https://openalex.org/T10454","display_name":"Optimal Power Flow Distribution","score":0.07750000059604645,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.5882999897003174},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5468000173568726},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5152000188827515},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.48489999771118164},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.4819999933242798},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4542999863624573},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.42890000343322754},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.42149999737739563},{"id":"https://openalex.org/keywords/network-architecture","display_name":"Network architecture","score":0.38420000672340393}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6017000079154968},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5882999897003174},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5468000173568726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5228999853134155},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5152000188827515},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.48489999771118164},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.4819999933242798},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4542999863624573},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.42890000343322754},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4203999936580658},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39649999141693115},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.38420000672340393},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.3418999910354614},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.3361999988555908},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.33070001006126404},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3021000027656555},{"id":"https://openalex.org/C175202392","wikidata":"https://www.wikidata.org/wiki/Q2434543","display_name":"Time delay neural network","level":3,"score":0.28540000319480896},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2791000008583069},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2775999903678894},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.34133/icomputing.0229","is_oa":true,"landing_page_url":"https://doi.org/10.34133/icomputing.0229","pdf_url":null,"source":{"id":"https://openalex.org/S4387281904","display_name":"Intelligent Computing","issn_l":"2771-5892","issn":["2771-5892"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Computing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0486c1eef02a4804a02f82110b36d022","is_oa":true,"landing_page_url":"https://doaj.org/article/0486c1eef02a4804a02f82110b36d022","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":"Intelligent Computing, Vol 4 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.34133/icomputing.0229","is_oa":true,"landing_page_url":"https://doi.org/10.34133/icomputing.0229","pdf_url":null,"source":{"id":"https://openalex.org/S4387281904","display_name":"Intelligent Computing","issn_l":"2771-5892","issn":["2771-5892"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W2063895100","https://openalex.org/W2068061051","https://openalex.org/W2102542251","https://openalex.org/W2153392920","https://openalex.org/W2157070880","https://openalex.org/W2194775991","https://openalex.org/W2343847222","https://openalex.org/W2563387647","https://openalex.org/W2591489243","https://openalex.org/W2812096095","https://openalex.org/W2885144346","https://openalex.org/W2905833087","https://openalex.org/W2961144751","https://openalex.org/W2962810718","https://openalex.org/W2963946985","https://openalex.org/W2964051675","https://openalex.org/W2981406437","https://openalex.org/W3000881061","https://openalex.org/W3013310686","https://openalex.org/W3015665983","https://openalex.org/W3174844646","https://openalex.org/W3175546444","https://openalex.org/W3176772026","https://openalex.org/W4200625991","https://openalex.org/W4223482256","https://openalex.org/W4285263040","https://openalex.org/W4309609199","https://openalex.org/W4309771870","https://openalex.org/W4313413157","https://openalex.org/W4318320897","https://openalex.org/W4318407581","https://openalex.org/W4321850199","https://openalex.org/W4362709141","https://openalex.org/W4381609771","https://openalex.org/W4386702673","https://openalex.org/W4390577884","https://openalex.org/W4391853495","https://openalex.org/W4393144919","https://openalex.org/W4393157099","https://openalex.org/W4399052547","https://openalex.org/W4401328210","https://openalex.org/W4402043250","https://openalex.org/W4404016449","https://openalex.org/W4406457768","https://openalex.org/W4407361695","https://openalex.org/W4408100269"],"related_works":[],"abstract_inverted_index":{"Fault":[0],"location":[1,24],"is":[2,63],"an":[3,68,87],"essential":[4],"aspect":[5],"of":[6,163,175,181,191],"distribution":[7,170],"networks":[8,171],"for":[9,54,67,83,98,109],"safe":[10],"operation":[11],"and":[12,44,59],"power":[13],"supply.":[14],"Deep":[15],"learning-based":[16],"methods":[17,53],"have":[18],"achieved":[19],"favorable":[20],"success":[21],"in":[22,126],"fault":[23,99],"due":[25],"to":[26,47,64,124,142,146],"their":[27],"good":[28],"feature":[29],"extraction":[30],"capabilities.":[31],"In":[32,116,178],"particular,":[33],"the":[34,41,127,144,154,161,164,192],"graph":[35,89],"neural":[36,76,90],"network":[37,42],"(GNN)":[38],"can":[39,72],"exploit":[40],"topology":[43],"node":[45],"information":[46],"accurately":[48],"locate":[49],"faults.":[50],"However,":[51],"conventional":[52],"designing":[55],"GNNs":[56],"are":[57,121],"tedious":[58],"error-prone.":[60],"A":[61],"solution":[62],"automatically":[65],"search":[66,78,92,128],"efficient":[69],"GNN,":[70],"which":[71],"be":[73],"realized":[74],"by":[75],"architecture":[77,91],"(NAS).":[79],"To":[80,159],"achieve":[81,147],"NAS":[82],"GNNs,":[84],"we":[85,102,131,167],"propose":[86],"evolutionary":[88],"with":[93,137],"a":[94,105,133,138,173],"mask":[95,134],"predictor":[96,145],"(EGNAS-MP)":[97],"location.":[100],"Specifically,":[101],"first":[103],"design":[104,132],"variable-length":[106],"encoding":[107],"strategy":[108,141],"flexibly":[110],"representing":[111],"different":[112],"scale":[113],"candidate":[114],"architectures.":[115],"addition,":[117],"complementary":[118],"reproduction":[119],"operators":[120],"also":[122],"devised":[123],"assist":[125],"efficiency.":[129],"Furthermore,":[130],"mechanism":[135],"combined":[136],"progressive":[139],"fine-tuning":[140],"enable":[143],"accurate":[148],"fitness":[149],"value":[150],"predictions":[151],"while":[152],"minimizing":[153],"reliance":[155],"on":[156],"supervised":[157],"data.":[158],"validate":[160],"effectiveness":[162],"proposed":[165],"method,":[166],"simulate":[168],"2":[169],"under":[172],"variety":[174],"resistance":[176],"conditions.":[177],"both":[179],"sets":[180],"simulation":[182],"experiments,":[183],"EGNAS-MP":[184],"achieves":[185],"higher":[186],"accuracies":[187],"than":[188],"all":[189],"4":[190],"baseline":[193],"machine":[194],"learning":[195],"models,":[196],"thus":[197],"demonstrating":[198],"strong":[199],"generalization":[200],"ability":[201],"across":[202],"differing":[203],"topologies.":[204]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-28T00:00:00"}
