{"id":"https://openalex.org/W4399257652","doi":"https://doi.org/10.1145/3653804.3655993","title":"Lightweight Method for Adaptive Power Grid Operation Safety Control Model Based on Knowledge Distillation","display_name":"Lightweight Method for Adaptive Power Grid Operation Safety Control Model Based on Knowledge Distillation","publication_year":2024,"publication_date":"2024-01-19","ids":{"openalex":"https://openalex.org/W4399257652","doi":"https://doi.org/10.1145/3653804.3655993"},"language":"en","primary_location":{"id":"doi:10.1145/3653804.3655993","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3653804.3655993","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Computer Vision and Deep Learning","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/A5003223913","display_name":"Wei Wei","orcid":"https://orcid.org/0009-0005-4953-0680"},"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"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Wei","raw_affiliation_strings":["Grid Laboratory of Grid Advanced Computing and Applications, State Grid Smart Grid Research Institute Co.ltd., China"],"raw_orcid":"https://orcid.org/0009-0005-4953-0680","affiliations":[{"raw_affiliation_string":"Grid Laboratory of Grid Advanced Computing and Applications, State Grid Smart Grid Research Institute Co.ltd., China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059836458","display_name":"Yi Zhang","orcid":"https://orcid.org/0009-0009-2726-5977"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["Grid Laboratory of Grid Advanced Computing and Applications, State Grid Smart Grid Research Institute Co.ltd., China"],"raw_orcid":"https://orcid.org/0000-0002-9421-3626","affiliations":[{"raw_affiliation_string":"Grid Laboratory of Grid Advanced Computing and Applications, State Grid Smart Grid Research Institute Co.ltd., China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049576699","display_name":"Zexu Du","orcid":"https://orcid.org/0000-0003-2741-4724"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zexu Du","raw_affiliation_strings":["Grid Laboratory of Grid Advanced Computing and Applications, State Grid Smart Grid Research Institute Co.ltd., China"],"raw_orcid":"https://orcid.org/0000-0003-2741-4724","affiliations":[{"raw_affiliation_string":"Grid Laboratory of Grid Advanced Computing and Applications, State Grid Smart Grid Research Institute Co.ltd., China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040091490","display_name":"Zongbo Chu","orcid":"https://orcid.org/0009-0007-8499-2148"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongbo Chu","raw_affiliation_strings":["Grid Laboratory of Grid Advanced Computing and Applications, State Grid Smart Grid Research Institute Co.ltd., China"],"raw_orcid":"https://orcid.org/0009-0007-8499-2148","affiliations":[{"raw_affiliation_string":"Grid Laboratory of Grid Advanced Computing and Applications, State Grid Smart Grid Research Institute Co.ltd., China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100607251","display_name":"Guoliang Zhang","orcid":"https://orcid.org/0000-0001-7309-5344"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoliang Zhang","raw_affiliation_strings":["Grid Laboratory of Grid Advanced Computing and Applications, State Grid Smart Grid Research Institute Co.ltd., China"],"raw_orcid":"https://orcid.org/0000-0001-7309-5344","affiliations":[{"raw_affiliation_string":"Grid Laboratory of Grid Advanced Computing and Applications, State Grid Smart Grid Research Institute Co.ltd., China","institution_ids":["https://openalex.org/I17442442"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5003223913"],"corresponding_institution_ids":["https://openalex.org/I17442442"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06507568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9830999970436096,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12451","display_name":"Smart Grid and Power Systems","score":0.9794999957084656,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9745000004768372,"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":0.7841053605079651},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7593079805374146},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5433744192123413},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5267027020454407},{"id":"https://openalex.org/keywords/sort","display_name":"sort","score":0.5184154510498047},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5022263526916504},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49581870436668396},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4916883111000061},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47156235575675964},{"id":"https://openalex.org/keywords/overshoot","display_name":"Overshoot (microwave communication)","score":0.4676878750324249},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45666956901550293},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4549036920070648},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.4460926651954651},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41953808069229126},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.4102384150028229},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.12511560320854187}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7841053605079651},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7593079805374146},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5433744192123413},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5267027020454407},{"id":"https://openalex.org/C88548561","wikidata":"https://www.wikidata.org/wiki/Q347599","display_name":"sort","level":2,"score":0.5184154510498047},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5022263526916504},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49581870436668396},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4916883111000061},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47156235575675964},{"id":"https://openalex.org/C2780323453","wikidata":"https://www.wikidata.org/wiki/Q7113957","display_name":"Overshoot (microwave communication)","level":2,"score":0.4676878750324249},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45666956901550293},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4549036920070648},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.4460926651954651},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41953808069229126},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.4102384150028229},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.12511560320854187},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3653804.3655993","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3653804.3655993","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Computer Vision and Deep Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2058715873","https://openalex.org/W2951513317","https://openalex.org/W2963140444","https://openalex.org/W3034368386","https://openalex.org/W3138154797","https://openalex.org/W3213175553","https://openalex.org/W6929150435"],"related_works":["https://openalex.org/W2357124094","https://openalex.org/W2387399993","https://openalex.org/W2389739210","https://openalex.org/W2348924972","https://openalex.org/W2365736347","https://openalex.org/W2047454415","https://openalex.org/W2070040999","https://openalex.org/W2387293848","https://openalex.org/W2250140200","https://openalex.org/W3121791438"],"abstract_inverted_index":{"Safety":[0],"control":[1,15],"is":[2,63,76,96,110],"one":[3],"of":[4,59,69,83,93,121],"the":[5,56,60,67,70,79,99,103,107,114,119,133],"most":[6],"important":[7],"tasks":[8],"for":[9,31,102],"power":[10],"grid":[11],"operation.":[12],"However,":[13],"safety":[14],"and":[16,27,44,73,129,142,146],"risk":[17],"warning":[18],"models":[19],"with":[20],"high":[21],"accuracy":[22],"always":[23],"have":[24],"multitudinous":[25],"parameters":[26],"need":[28],"scaled":[29],"resources":[30],"calculation.":[32],"So":[33],"as":[34],"to":[35,65,86,98,112,117],"sort":[36],"out":[37],"this":[38],"problem,":[39],"we":[40],"proposed":[41],"a":[42,74],"novel":[43],"adaptive":[45,143],"model":[46,135],"lightweight":[47,134],"method":[48,139],"based":[49],"on":[50,125],"knowledge":[51],"distillation.":[52],"In":[53],"our":[54,138],"method,":[55],"intermediate":[57],"features":[58],"teacher":[61,84,94],"network":[62,72,85,95],"utilized":[64],"guide":[66],"learning":[68],"student":[71],"regressor":[75,104],"introduced":[77],"behind":[78],"selected":[80],"middle":[81],"layer":[82],"realize":[87],"dimension":[88],"match.":[89],"The":[90],"prediction":[91,108],"confidence":[92,109],"mapped":[97],"feature":[100,144],"space":[101],"initialization.":[105],"Besides,":[106],"used":[111],"construct":[113],"distillation":[115],"temperature":[116],"improve":[118],"adaptability":[120],"information":[122],"transfer.":[123],"Experiments":[124],"ImageNet,":[126],"CIFAR":[127],"100":[128],"Grid-specific":[130],"datasets":[131],"demonstrate":[132],"obtained":[136],"by":[137],"possesses":[140],"powerful":[141],"extraction":[145],"representation":[147],"ability.":[148]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}