{"id":"https://openalex.org/W4386806702","doi":"https://doi.org/10.1142/s0218194023500560","title":"GTFP: Network Fault Prediction Based on Graph and Time Series","display_name":"GTFP: Network Fault Prediction Based on Graph and Time Series","publication_year":2023,"publication_date":"2023-09-16","ids":{"openalex":"https://openalex.org/W4386806702","doi":"https://doi.org/10.1142/s0218194023500560"},"language":"en","primary_location":{"id":"doi:10.1142/s0218194023500560","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218194023500560","pdf_url":null,"source":{"id":"https://openalex.org/S131442419","display_name":"International Journal of Software Engineering and Knowledge Engineering","issn_l":"0218-1940","issn":["0218-1940","1793-6403"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Software Engineering and Knowledge Engineering","raw_type":"journal-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/A5101526079","display_name":"Zhongliang Li","orcid":"https://orcid.org/0009-0007-5848-6540"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongliang Li","raw_affiliation_strings":["College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, P.\u00a0R.\u00a0China"],"raw_orcid":"https://orcid.org/0009-0007-5848-6540","affiliations":[{"raw_affiliation_string":"College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101520213","display_name":"Junjun Ding","orcid":"https://orcid.org/0009-0009-8372-9094"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjun Ding","raw_affiliation_strings":["School of Cyber Science and Engineering, Southeast University, Nanjing 211189, P.\u00a0R.\u00a0China"],"raw_orcid":"https://orcid.org/0009-0009-8372-9094","affiliations":[{"raw_affiliation_string":"School of Cyber Science and Engineering, Southeast University, Nanjing 211189, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083090411","display_name":"Zongming Ma","orcid":"https://orcid.org/0000-0003-2401-0177"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zongming Ma","raw_affiliation_strings":["College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, P.\u00a0R.\u00a0China"],"raw_orcid":"https://orcid.org/0000-0001-7780-6473","affiliations":[{"raw_affiliation_string":"College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1755,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.47733475,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"34","issue":"03","first_page":"489","last_page":"510"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9750000238418579,"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"}},"topics":[{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9750000238418579,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9674999713897705,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9429000020027161,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7464649081230164},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5702210068702698},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48466426134109497},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.4816214442253113},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4807562530040741},{"id":"https://openalex.org/keywords/alarm","display_name":"ALARM","score":0.45412886142730713},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.452340304851532},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43628990650177},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4298640489578247},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4000247120857239},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1945570707321167},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13528123497962952},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.08750489354133606}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7464649081230164},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5702210068702698},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48466426134109497},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.4816214442253113},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4807562530040741},{"id":"https://openalex.org/C2779119184","wikidata":"https://www.wikidata.org/wiki/Q294350","display_name":"ALARM","level":2,"score":0.45412886142730713},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.452340304851532},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43628990650177},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4298640489578247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4000247120857239},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1945570707321167},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13528123497962952},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.08750489354133606},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218194023500560","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218194023500560","pdf_url":null,"source":{"id":"https://openalex.org/S131442419","display_name":"International Journal of Software Engineering and Knowledge Engineering","issn_l":"0218-1940","issn":["0218-1940","1793-6403"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Software Engineering and Knowledge Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.6899999976158142,"display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1893433911","https://openalex.org/W1985629328","https://openalex.org/W2144720143","https://openalex.org/W2161415693","https://openalex.org/W2395638974","https://openalex.org/W2580840020","https://openalex.org/W2807021761","https://openalex.org/W2968162821","https://openalex.org/W2981993535","https://openalex.org/W3036218864","https://openalex.org/W3083550439","https://openalex.org/W3089516618","https://openalex.org/W3099845770","https://openalex.org/W3100848837","https://openalex.org/W3118853040","https://openalex.org/W3127109520","https://openalex.org/W3135827211","https://openalex.org/W3194400333","https://openalex.org/W3211596736","https://openalex.org/W4200448706","https://openalex.org/W4206159997","https://openalex.org/W4229366669","https://openalex.org/W4232606520","https://openalex.org/W4283741955","https://openalex.org/W4309226430","https://openalex.org/W4316021877"],"related_works":["https://openalex.org/W2731305060","https://openalex.org/W1584123598","https://openalex.org/W2732807254","https://openalex.org/W2372003537","https://openalex.org/W2587670262","https://openalex.org/W3091941553","https://openalex.org/W2366730739","https://openalex.org/W4378419970","https://openalex.org/W3121346907","https://openalex.org/W4379535633"],"abstract_inverted_index":{"With":[0],"the":[1,7,14,17,20,33,49,63,70,77,88,136,142,152,157,169,174,178,182,186,189,193,196,201,204,219,224,238],"explosion":[2],"of":[3,16,22,35,44,51,65,114,130,177,185,192,200,227,241],"5G":[4],"network":[5,8,18,45,52,80,84,115,134,179,197],"scale,":[6],"structure":[9],"becomes":[10],"increasingly":[11],"complex.":[12],"During":[13],"operation":[15],"devices,":[19],"probability":[21],"anomalies":[23],"or":[24],"faults":[25,29,46,158],"increases":[26],"accordingly.":[27],"Network":[28,91],"may":[30],"lead":[31],"to":[32,73,82,94,156,167,212],"disappearance":[34],"important":[36],"information":[37],"and":[38,54,68,87,108,124,135,195],"cause":[39],"unpredictable":[40],"losses.":[41],"The":[42],"prediction":[43],"can":[47],"enhance":[48],"quality":[50],"services":[53],"reduce":[55],"economic":[56],"loss.":[57],"In":[58],"this":[59],"paper,":[60],"we":[61,101,149,163,209],"propose":[62,102],"concept":[64],"4D":[66],"features":[67,176,184,191,199],"use":[69,210],"BERT":[71],"algorithm":[72,81,93,129],"extract":[74,83,95,168],"semantic":[75,183],"features,":[76,172],"graph":[78,132],"neural":[79,133],"topology":[85,198],"information,":[86,181],"Temporal":[89],"Convolutional":[90],"(TCN)":[92],"time":[96],"series.":[97],"Based":[98],"on":[99,106,122,218,223],"this,":[100],"Fault":[103],"Prediction":[104],"based":[105,121,217],"GraphSage":[107,123],"TCN":[109,125,137],"(GTFP),":[110],"an":[111],"end-to-end":[112],"solution":[113,140],"fault":[116,215,242],"alarm":[117,144,153,171,180,187,225,243],"prediction,":[118],"which":[119],"is":[120],"(GTCN),":[126],"a":[127,131,228],"hybrid":[128],"model.":[138],"Our":[139],"takes":[141],"historical":[143],"data":[145,160,226],"as":[146],"input.":[147],"First,":[148],"filter":[150],"out":[151],"noises":[154],"irrelevant":[155],"through":[159],"cleaning.":[161],"Then,":[162],"employ":[164],"feature":[165],"engineering":[166],"valid":[170],"including":[173],"statistical":[175],"texts,":[188],"sequential":[190],"alarms":[194,205,216],"nodes":[202],"where":[203],"are":[206],"located.":[207],"Finally,":[208],"GTCN":[211],"predict":[213],"future":[214],"extracted":[220],"features.":[221],"Experiments":[222],"real":[229],"service":[230],"system":[231],"show":[232],"that":[233],"GTFP":[234],"performs":[235],"better":[236],"than":[237],"state-of-the-art":[239],"algorithms":[240],"prediction.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
