{"id":"https://openalex.org/W4386495233","doi":"https://doi.org/10.1109/access.2023.3313003","title":"A Graph Deep Learning-Based Fault Detection and Positioning Method for Internet Communication Networks","display_name":"A Graph Deep Learning-Based Fault Detection and Positioning Method for Internet Communication Networks","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386495233","doi":"https://doi.org/10.1109/access.2023.3313003"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3313003","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3313003","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10243017.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10243017.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100357640","display_name":"Xiaoyu Wang","orcid":"https://orcid.org/0000-0003-1419-1904"},"institutions":[{"id":"https://openalex.org/I83519826","display_name":"Nanjing Medical University","ror":"https://ror.org/059gcgy73","country_code":"CN","type":"education","lineage":["https://openalex.org/I83519826"]},{"id":"https://openalex.org/I4210109791","display_name":"Nanjing Brain Hospital","ror":"https://ror.org/01wcx2305","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210109791"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoyu Wang","raw_affiliation_strings":["Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China","institution_ids":["https://openalex.org/I4210109791","https://openalex.org/I83519826"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081269670","display_name":"Zixuan Fu","orcid":"https://orcid.org/0000-0002-0242-673X"},"institutions":[{"id":"https://openalex.org/I4210109791","display_name":"Nanjing Brain Hospital","ror":"https://ror.org/01wcx2305","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210109791"]},{"id":"https://openalex.org/I83519826","display_name":"Nanjing Medical University","ror":"https://ror.org/059gcgy73","country_code":"CN","type":"education","lineage":["https://openalex.org/I83519826"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixuan Fu","raw_affiliation_strings":["Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China","institution_ids":["https://openalex.org/I4210109791","https://openalex.org/I83519826"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021811794","display_name":"Xiaofei Li","orcid":"https://orcid.org/0009-0000-7217-0242"},"institutions":[{"id":"https://openalex.org/I83519826","display_name":"Nanjing Medical University","ror":"https://ror.org/059gcgy73","country_code":"CN","type":"education","lineage":["https://openalex.org/I83519826"]},{"id":"https://openalex.org/I4210109791","display_name":"Nanjing Brain Hospital","ror":"https://ror.org/01wcx2305","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210109791"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofei Li","raw_affiliation_strings":["Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China","institution_ids":["https://openalex.org/I4210109791","https://openalex.org/I83519826"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100357640"],"corresponding_institution_ids":["https://openalex.org/I4210109791","https://openalex.org/I83519826"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6686,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.68831014,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"11","issue":null,"first_page":"102261","last_page":"102270"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13918","display_name":"Advanced Data and IoT Technologies","score":0.9948999881744385,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.9948999881744385,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.8129817247390747},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5891783833503723},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5400498509407043},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.5309673547744751},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.5048301815986633},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4760596454143524},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.45849454402923584},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4220521152019501},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3646343946456909},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3466585874557495},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3390619158744812},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2902088165283203},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.20928150415420532}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8129817247390747},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5891783833503723},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5400498509407043},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.5309673547744751},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.5048301815986633},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4760596454143524},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.45849454402923584},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4220521152019501},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3646343946456909},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3466585874557495},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3390619158744812},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2902088165283203},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20928150415420532},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3313003","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3313003","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10243017.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0680e0c151b94e2baed88057f7d6471c","is_oa":true,"landing_page_url":"https://doaj.org/article/0680e0c151b94e2baed88057f7d6471c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 102261-102270 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3313003","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3313003","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10243017.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386495233.pdf","grobid_xml":"https://content.openalex.org/works/W4386495233.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W2893263387","https://openalex.org/W2911027487","https://openalex.org/W2918117471","https://openalex.org/W2937353049","https://openalex.org/W2976140009","https://openalex.org/W2996165145","https://openalex.org/W3028559839","https://openalex.org/W3029169116","https://openalex.org/W3035300658","https://openalex.org/W3048221011","https://openalex.org/W3084473474","https://openalex.org/W3122026038","https://openalex.org/W3139414259","https://openalex.org/W3153733584","https://openalex.org/W3156161181","https://openalex.org/W3162357584","https://openalex.org/W3170516065","https://openalex.org/W3172408309","https://openalex.org/W3195347552","https://openalex.org/W3209489733","https://openalex.org/W3216875638","https://openalex.org/W4200047377","https://openalex.org/W4200448706","https://openalex.org/W4226199491","https://openalex.org/W4239296861","https://openalex.org/W4285142610","https://openalex.org/W4292245961","https://openalex.org/W4293731782","https://openalex.org/W4307638870","https://openalex.org/W4312890993","https://openalex.org/W4312959111","https://openalex.org/W4320001385","https://openalex.org/W4323797675","https://openalex.org/W4366492959","https://openalex.org/W4377235461","https://openalex.org/W4378194703"],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W4223943233","https://openalex.org/W4312200629","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W4380086463","https://openalex.org/W4225161397","https://openalex.org/W3014300295","https://openalex.org/W3164822677","https://openalex.org/W2795261237"],"abstract_inverted_index":{"In":[0,56],"modern":[1],"smart":[2],"cities,":[3],"the":[4,32,59,97,100,129,132,153,159,180,201,214],"scale":[5],"of":[6,26,41,45,125,152,179,195,207,216],"urban":[7,62],"backbone":[8,63,126],"networks":[9],"used":[10],"to":[11,28,106,117,140,149],"provide":[12],"Internet":[13,93,111],"communication":[14,94,112],"environment":[15],"are":[16,77,147],"constantly":[17],"increasing.":[18],"When":[19],"faults":[20,42],"occur,":[21],"it":[22],"usually":[23],"takes":[24],"lots":[25],"efforts":[27],"detect":[29],"and":[30,39,75,89,135],"locate":[31],"faults.":[33],"As":[34],"a":[35,50,68,82],"result,":[36],"automatic":[37],"detection":[38,88,134,168],"positioning":[40,90,136],"with":[43],"use":[44],"intelligent":[46],"algorithms":[47],"have":[48],"been":[49],"practical":[51],"demand":[52],"in":[53,71,165,174,187,200],"this":[54,57,80,188],"area.":[55],"paper,":[58],"complicated":[60],"whole":[61],"network":[64,103],"is":[65,104,115,138,190],"viewed":[66],"as":[67,169,171],"graph-level":[69,108],"object,":[70],"which":[72],"massive":[73],"nodes":[74],"edges":[76],"involved.":[78],"On":[79],"basis,":[81],"two-stage":[83,181],"graph":[84,101,182,209],"deep":[85,183,210],"learning-based":[86],"fault":[87,133,175],"method":[91,161],"for":[92,122],"networks.":[95,113,127],"For":[96,128],"first":[98],"stage,":[99,131],"neural":[102],"employed":[105],"extract":[107],"features":[109],"from":[110],"This":[114],"expected":[116],"obtain":[118],"proper":[119],"feature":[120],"representation":[121],"core":[123],"characteristics":[124],"second":[130],"algorithm":[137,185,218],"formulated":[139],"output":[141],"final":[142],"results.":[143],"At":[144],"last,":[145],"experiments":[146],"conducted":[148],"assess":[150],"performance":[151,164],"proposal.":[154],"The":[155,177],"results":[156],"show":[157],"that":[158,194,206],"proposed":[160,186],"has":[162],"good":[163],"abnormal":[166],"node":[167],"well":[170],"high":[172],"accuracy":[173,178,215],"positioning.":[176],"learning":[184,211],"chapter":[189],"much":[191],"higher":[192],"than":[193,205],"KNN":[196],"algorithm,":[197,212],"reaching":[198],"96.5%":[199],"end,":[202],"slightly":[203],"lower":[204],"pure":[208],"while":[213],"IRBFG":[217],"can":[219],"only":[220],"reach":[221],"92%.":[222]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}