{"id":"https://openalex.org/W4200233747","doi":"https://doi.org/10.3233/faia210400","title":"Research on Identification of Power Grid Weakness Based on Bayesian Inference","display_name":"Research on Identification of Power Grid Weakness Based on Bayesian Inference","publication_year":2021,"publication_date":"2021-12-22","ids":{"openalex":"https://openalex.org/W4200233747","doi":"https://doi.org/10.3233/faia210400"},"language":"en","primary_location":{"id":"doi:10.3233/faia210400","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia210400","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA210400","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA210400","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103246390","display_name":"Jiang Hu","orcid":"https://orcid.org/0000-0003-1157-7799"},"institutions":[{"id":"https://openalex.org/I4210145500","display_name":"Guizhou Electric Power Design and Research Institute","ror":"https://ror.org/055f13495","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145500"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiang Hu","raw_affiliation_strings":["Grid Planning & Research Center, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, 550003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Grid Planning & Research Center, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, 550003, China","institution_ids":["https://openalex.org/I4210145500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100317994","display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-7015-7335"},"institutions":[{"id":"https://openalex.org/I4210145500","display_name":"Guizhou Electric Power Design and Research Institute","ror":"https://ror.org/055f13495","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145500"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["Guiyang Power Supply Bureau, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, 550003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guiyang Power Supply Bureau, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, 550003, China","institution_ids":["https://openalex.org/I4210145500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085596690","display_name":"Wenxia Liu","orcid":"https://orcid.org/0000-0002-0784-018X"},"institutions":[{"id":"https://openalex.org/I4210145500","display_name":"Guizhou Electric Power Design and Research Institute","ror":"https://ror.org/055f13495","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145500"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxia Liu","raw_affiliation_strings":["Grid Planning & Research Center, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, 550003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Grid Planning & Research Center, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, 550003, China","institution_ids":["https://openalex.org/I4210145500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057396599","display_name":"Xianggang He","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145500","display_name":"Guizhou Electric Power Design and Research Institute","ror":"https://ror.org/055f13495","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145500"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianggang He","raw_affiliation_strings":["Grid Planning & Research Center, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, 550003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Grid Planning & Research Center, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, 550003, China","institution_ids":["https://openalex.org/I4210145500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036488225","display_name":"Yu Zhang","orcid":"https://orcid.org/0000-0001-6638-6442"},"institutions":[{"id":"https://openalex.org/I4210145500","display_name":"Guizhou Electric Power Design and Research Institute","ror":"https://ror.org/055f13495","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145500"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zhang","raw_affiliation_strings":["Grid Planning & Research Center, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, 550003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Grid Planning & Research Center, Guizhou Power Grid Co., Ltd., Guiyang, Guizhou, 550003, China","institution_ids":["https://openalex.org/I4210145500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103246390"],"corresponding_institution_ids":["https://openalex.org/I4210145500"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33936886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14276","display_name":"Power Systems and Technologies","score":0.9718000292778015,"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"}},"topics":[{"id":"https://openalex.org/T14276","display_name":"Power Systems and Technologies","score":0.9718000292778015,"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/T12451","display_name":"Smart Grid and Power Systems","score":0.9666000008583069,"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9302999973297119,"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/correctness","display_name":"Correctness","score":0.6473994851112366},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6268450021743774},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.6093600392341614},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.6069544553756714},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5278453826904297},{"id":"https://openalex.org/keywords/chain-rule","display_name":"Chain rule (probability)","score":0.4827825129032135},{"id":"https://openalex.org/keywords/conditional-probability","display_name":"Conditional probability","score":0.4479198753833771},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.443369060754776},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43345844745635986},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.42655789852142334},{"id":"https://openalex.org/keywords/law-of-total-probability","display_name":"Law of total probability","score":0.30662477016448975},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3012402057647705},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28085821866989136},{"id":"https://openalex.org/keywords/posterior-probability","display_name":"Posterior probability","score":0.25676631927490234},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1717890202999115},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1294889748096466}],"concepts":[{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.6473994851112366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6268450021743774},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.6093600392341614},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.6069544553756714},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5278453826904297},{"id":"https://openalex.org/C33825631","wikidata":"https://www.wikidata.org/wiki/Q17004731","display_name":"Chain rule (probability)","level":5,"score":0.4827825129032135},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.4479198753833771},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.443369060754776},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43345844745635986},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.42655789852142334},{"id":"https://openalex.org/C49698424","wikidata":"https://www.wikidata.org/wiki/Q1989192","display_name":"Law of total probability","level":4,"score":0.30662477016448975},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3012402057647705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28085821866989136},{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.25676631927490234},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1717890202999115},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1294889748096466},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia210400","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia210400","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA210400","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia210400","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia210400","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA210400","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4200233747.pdf","grobid_xml":"https://content.openalex.org/works/W4200233747.grobid-xml"},"referenced_works_count":4,"referenced_works":["https://openalex.org/W1965424194","https://openalex.org/W2052444112","https://openalex.org/W2381162371","https://openalex.org/W2762475736"],"related_works":["https://openalex.org/W2041511828","https://openalex.org/W2285782125","https://openalex.org/W2136165559","https://openalex.org/W4235623166","https://openalex.org/W2900754349","https://openalex.org/W3111599513","https://openalex.org/W4383821505","https://openalex.org/W4250630220","https://openalex.org/W2348834827","https://openalex.org/W2330332587"],"abstract_inverted_index":{"With":[0],"the":[1,7,23,27,31,38,44,69,76,89,94,98,106,112,118,128,133,146],"gradual":[2],"reform":[3],"and":[4,21,35,50,97,132,143,156],"development":[5],"of":[6,12,26,37,93,124,145],"power":[8,28,39,45,81,158],"grid,":[9],"it":[10],"is":[11,85,102,130,139],"great":[13],"significance":[14],"to":[15,18,75,88],"study":[16],"how":[17],"effectively":[19],"identify":[20],"evaluate":[22],"weak":[24,58,136],"links":[25],"grid":[29,95,107,159],"for":[30],"actual":[32],"planning,":[33],"construction,":[34],"operation":[36,52,91],"grid.":[40],"This":[41],"paper":[42],"analyzed":[43],"grid\u2019s":[46],"historical":[47,90],"component":[48],"data":[49],"real-time":[51],"state":[53],"parameters.":[54],"We":[55],"established":[56],"a":[57],"link":[59,137],"identification":[60],"model":[61],"based":[62,104],"on":[63,105],"Bayesian":[64,72,119],"reasoning.":[65],"Firstly,":[66],"we":[67,110],"constructed":[68],"node":[70],"branch":[71],"network":[73,77,129],"according":[74,87],"topology":[78],"relationship.":[79],"The":[80,121,141],"transmission":[82],"distribution":[83],"factor":[84],"modified":[86],"load":[92],"components,":[96],"conditional":[99],"probability":[100,135],"table":[101],"calculated":[103],"structure;":[108],"finally,":[109],"used":[111],"maximum":[113,134],"possible":[114],"explanation":[115],"algorithm":[116],"in":[117,127],"network.":[120],"weakness":[122],"degree":[123],"all":[125],"components":[126],"calculated,":[131],"sequence":[138],"obtained.":[140],"correctness":[142],"effectiveness":[144],"proposed":[147],"method":[148],"are":[149],"verified":[150],"by":[151],"IEEE":[152],"39":[153],"bus":[154],"simulation":[155],"regional":[157],"data.":[160]},"counts_by_year":[],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}
