{"id":"https://openalex.org/W4389401231","doi":"https://doi.org/10.1109/powercon58120.2023.10331066","title":"Text Classification of Cable Inspection Based on Word Embedding and Recurrent Convolutional Neural Network","display_name":"Text Classification of Cable Inspection Based on Word Embedding and Recurrent Convolutional Neural Network","publication_year":2023,"publication_date":"2023-09-21","ids":{"openalex":"https://openalex.org/W4389401231","doi":"https://doi.org/10.1109/powercon58120.2023.10331066"},"language":"en","primary_location":{"id":"doi:10.1109/powercon58120.2023.10331066","doi":"https://doi.org/10.1109/powercon58120.2023.10331066","is_oa":false,"landing_page_url":"https://doi.org/10.1109/powercon58120.2023.10331066","pdf_url":null,"source":{"id":"https://openalex.org/S4363607772","display_name":"International Conference on Power System Technology (POWERCON)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Power System Technology (PowerCon)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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":null,"display_name":"Yuli Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4392738113","display_name":"China Electric Power Research Institute","ror":"https://ror.org/05ehpzy81","country_code":"CN","type":"facility","lineage":["https://openalex.org/I17442442","https://openalex.org/I4392738113"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuli Wang","raw_affiliation_strings":["China Electric Power Research Institute Co., Ltd., Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Electric Power Research Institute Co., Ltd., Wuhan, China","institution_ids":["https://openalex.org/I4392738113"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ge Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4392738113","display_name":"China Electric Power Research Institute","ror":"https://ror.org/05ehpzy81","country_code":"CN","type":"facility","lineage":["https://openalex.org/I17442442","https://openalex.org/I4392738113"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Wang","raw_affiliation_strings":["China Electric Power Research Institute Co., Ltd., Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Electric Power Research Institute Co., Ltd., Wuhan, China","institution_ids":["https://openalex.org/I4392738113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101585746","display_name":"Yifan He","orcid":"https://orcid.org/0009-0001-8664-037X","observed_orcids":["https://orcid.org/0009-0001-8664-037X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yifan He","raw_affiliation_strings":["Zhejiang Electric Power Research Institute Co., Ltd, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Electric Power Research Institute Co., Ltd, Hangzhou, China","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Guangzhen Ren","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405270619","display_name":"State Grid Zhejiang Electric Power Company (China)","ror":"https://ror.org/011kx0q31","country_code":"CN","type":"company","lineage":["https://openalex.org/I4405270619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangzhen Ren","raw_affiliation_strings":["Zhejiang Electric Power Co., Ltd, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang Electric Power Co., Ltd, Hangzhou, China","institution_ids":["https://openalex.org/I4405270619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.35246896,"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/T13715","display_name":"Power Line Inspection Robots","score":0.453900009393692,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T13715","display_name":"Power Line Inspection Robots","score":0.453900009393692,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T10028","display_name":"Topic Modeling","score":0.2442999929189682,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.1720000058412552,"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/power-distribution-equipment","display_name":"power distribution equipment","score":0.7940000295639038},{"id":"https://openalex.org/keywords/environmental-risk-identification","display_name":"environmental risk identification","score":0.6169999837875366},{"id":"https://openalex.org/keywords/word-embeddings","display_name":"word embeddings","score":0.777999997138977},{"id":"https://openalex.org/keywords/recurrent-convolutional-neural-network","display_name":"recurrent convolutional neural network","score":0.9869999885559082},{"id":"https://openalex.org/keywords/pre-trained-word-vectors","display_name":"pre-trained word vectors","score":0.7620000243186951},{"id":"https://openalex.org/keywords/local-and-global-feature-extraction","display_name":"local and global feature extraction","score":0.6859999895095825},{"id":"https://openalex.org/keywords/power-cable-condition-monitoring","display_name":"power cable condition monitoring","score":0.4490000009536743},{"id":"https://openalex.org/keywords/operation-and-maintenance-cost-reduction","display_name":"operation and maintenance cost reduction","score":0.7279999852180481}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.754683256149292},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7411904335021973},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6784673929214478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5506061911582947},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5294941067695618},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4868725836277008},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45451778173446655},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4368087947368622},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.42994821071624756},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4120943248271942},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41201046109199524},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3769635558128357},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37526771426200867},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07288557291030884},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/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/powercon58120.2023.10331066","doi":"https://doi.org/10.1109/powercon58120.2023.10331066","is_oa":false,"landing_page_url":"https://doi.org/10.1109/powercon58120.2023.10331066","pdf_url":null,"source":{"id":"https://openalex.org/S4363607772","display_name":"International Conference on Power System Technology (POWERCON)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Power System Technology (PowerCon)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.7207000255584717}],"study_designs":[],"awards":[{"id":"https://openalex.org/G5703513030","display_name":null,"funder_award_id":"5400-202119145A-0-0-00","funder_id":"https://openalex.org/F4320326707","funder_display_name":"State Grid Corporation of China"}],"funders":[{"id":"https://openalex.org/F4320326707","display_name":"State Grid Corporation of China","ror":"https://ror.org/05twwhs70"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W947140380","https://openalex.org/W2937815589","https://openalex.org/W2944852028","https://openalex.org/W2990625131"],"related_works":["https://openalex.org/W4225350644","https://openalex.org/W2958444310","https://openalex.org/W3029689284","https://openalex.org/W2921356835","https://openalex.org/W2908226966","https://openalex.org/W4297238266","https://openalex.org/W4220768569","https://openalex.org/W2970257222","https://openalex.org/W4401190397","https://openalex.org/W4211028272"],"abstract_inverted_index":{"Power":[0],"distribution":[1,26,64,220],"equipment":[2,27],"is":[3,28,35,38,88,176],"vulnerable":[4],"to":[5,44,51,90],"comprehensive":[6],"impacts":[7],"such":[8],"as":[9,177,179],"natural":[10],"disasters,":[11],"human":[12],"activities,":[13],"tree":[14],"barriers,":[15],"and":[16,66,69,83,108,126,156,172,187,203,214],"bird":[17],"damage":[18],"during":[19],"operation.":[20],"However,":[21],"the":[22,31,41,59,92,98,105,111,117,127,135,142,148,164,184,200,219],"volume":[23],"of":[24,40,55,62,95,167,206],"power":[25,63],"large":[29],"while":[30],"online":[32],"monitoring":[33],"coverage":[34],"low.":[36],"Inspection":[37],"one":[39],"main":[42],"means":[43],"obtain":[45],"its":[46],"operating":[47],"status.":[48],"In":[49],"order":[50],"make":[52],"full":[53],"use":[54],"patrol":[56,169,207],"text,":[57,208],"enhance":[58],"operation":[60,68],"stability":[61],"equipment,":[65],"reduce":[67],"maintenance":[70],"costs,":[71],"a":[72],"classification":[73,149,171],"method":[74],"for":[75,218],"cable":[76,221],"inspection":[77,99],"texts":[78],"based":[79],"on":[80],"word":[81,112,137,185],"embedding":[82,186],"recurrent":[84,118],"convolutional":[85,119,189],"neural":[86,120,190],"network":[87,121,191],"proposed":[89,193],"identify":[91],"environmental":[93],"risks":[94],"cables.":[96],"First,":[97],"text":[100,128,170],"was":[101,124,129,145],"preprocessed":[102],"by":[103,140,153],"eliminating":[104],"punctuation":[106],"marks":[107],"annotations,":[109],"with":[110,134],"vector":[113,133,138],"model":[114,123,144,150,192],"pre-trained.":[115],"Then":[116],"(RCNN)":[122],"built":[125],"embedded":[130],"into":[131],"feature":[132],"pre-trained":[136],"model,":[139],"which":[141,181],"RCNN":[143],"trained.":[146],"Finally,":[147],"were":[151],"evaluated":[152],"F1":[154,165],"value":[155,166],"accuracy":[157],"rate.":[158],"The":[159],"example":[160],"analysis":[161,224],"shows":[162],"that":[163,183],"circuit":[168],"recognition":[173],"evaluation":[174],"index":[175],"high":[178],"0.8771,":[180],"indicates":[182],"circular":[188],"in":[194],"this":[195],"paper":[196],"can":[197],"effectively":[198],"extract":[199],"local":[201],"features":[202,205],"global":[204],"achieve":[209],"accurate":[210],"risk":[211],"level":[212],"classification,":[213],"provide":[215],"algorithm":[216],"support":[217],"Big":[222],"data":[223],"system.":[225]},"counts_by_year":[],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2023-12-07T00:00:00"}
