{"id":"https://openalex.org/W2967467847","doi":"https://doi.org/10.1109/access.2019.2935628","title":"Incremental Prediction Model of Disk Failures Based on the Density Metric of Edge Samples","display_name":"Incremental Prediction Model of Disk Failures Based on the Density Metric of Edge Samples","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2967467847","doi":"https://doi.org/10.1109/access.2019.2935628","mag":"2967467847"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2935628","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2935628","pdf_url":null,"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://doi.org/10.1109/access.2019.2935628","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103162506","display_name":"Xin Gao","orcid":"https://orcid.org/0000-0002-7760-0915"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Gao","raw_affiliation_strings":["School of Automation, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7760-0915","affiliations":[{"raw_affiliation_string":"School of Automation, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055597026","display_name":"Sen Zha","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Zha","raw_affiliation_strings":["School of Automation, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101935387","display_name":"Xinpeng Li","orcid":"https://orcid.org/0009-0003-5129-511X"},"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":"Xinpeng Li","raw_affiliation_strings":["State Grid Corporation of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Corporation of China, Beijing, China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081115024","display_name":"Bo Yan","orcid":"https://orcid.org/0000-0003-0256-9682"},"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":"Bo Yan","raw_affiliation_strings":["State Grid Jibei Electric Power Company Limited, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Jibei Electric Power Company Limited, Beijing, China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028829568","display_name":"Xiao Jing","orcid":"https://orcid.org/0000-0001-6825-9113"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Jing","raw_affiliation_strings":["School of Automation, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100717913","display_name":"Junliang Li","orcid":"https://orcid.org/0000-0002-0524-3840"},"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":"Junliang Li","raw_affiliation_strings":["Nari Group Corporation (State Grid Electric Power Research Institute), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nari Group Corporation (State Grid Electric Power Research Institute), Beijing, China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101151056","display_name":"Jianhang Xu","orcid":null},"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":"Jianhang Xu","raw_affiliation_strings":["Nari Group Corporation (State Grid Electric Power Research Institute), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nari Group Corporation (State Grid Electric Power Research Institute), Beijing, China","institution_ids":["https://openalex.org/I17442442"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5103162506"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.1614,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.84397054,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"7","issue":null,"first_page":"114285","last_page":"114296"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987000226974487,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987000226974487,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9855999946594238,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9713000059127808,"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/metric","display_name":"Metric (unit)","score":0.7066998481750488},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6386499404907227},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5853111147880554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18659564852714539},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08282947540283203}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7066998481750488},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6386499404907227},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5853111147880554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18659564852714539},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08282947540283203},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2935628","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2935628","pdf_url":null,"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:d9c7b9d9b2414a9da50b1d65e3c1ff1a","is_oa":true,"landing_page_url":"https://doaj.org/article/d9c7b9d9b2414a9da50b1d65e3c1ff1a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 114285-114296 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2935628","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2935628","pdf_url":null,"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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1786045870","https://openalex.org/W1990106316","https://openalex.org/W2052643920","https://openalex.org/W2119381450","https://openalex.org/W2122646361","https://openalex.org/W2123883612","https://openalex.org/W2153802732","https://openalex.org/W2282861635","https://openalex.org/W2295598076","https://openalex.org/W2507487910","https://openalex.org/W2509298940","https://openalex.org/W2541635437","https://openalex.org/W2616332741","https://openalex.org/W2783205364","https://openalex.org/W2793167745","https://openalex.org/W2807547163","https://openalex.org/W2808462996","https://openalex.org/W2891130433","https://openalex.org/W2903403561","https://openalex.org/W2908031023","https://openalex.org/W2910364449","https://openalex.org/W2913119932","https://openalex.org/W2917459525","https://openalex.org/W4254182148","https://openalex.org/W6677844719"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"Disks":[0],"are":[1,163,220,236,240],"the":[2,21,30,35,43,51,57,68,88,101,109,114,124,129,144,149,152,155,158,166,173,178,181,185,189,192,197,200,216,231,234,243,259,270,279,283,289],"main":[3],"equipment":[4],"for":[5,20,50],"data":[6,9,55],"storage":[7],"in":[8,34,230],"centers.":[10],"The":[11,137,238,255],"prediction":[12,85],"of":[13,17,25,29,45,53,70,91,104,113,128,140,143,151,154,169,172,191,199,204],"disk":[14,36,83,224,285],"failure":[15,84],"is":[16,39,97,118],"great":[18],"significance":[19],"reliability":[22],"and":[23,47,73,123,196,226,245,252,267,269],"security":[24],"data.":[26],"On":[27],"account":[28],"few":[31],"abnormal":[32,54,141,170],"samples":[33],"datasets,":[37],"it":[38],"difficult":[40],"to":[41,188,223],"satisfy":[42],"requirement":[44],"supervised":[46],"semi-supervised":[48],"algorithms":[49,59,262],"number":[52],"while":[56],"unsupervised":[58,261],"have":[60],"poor":[61],"performance":[62,294],"on":[63,242,282,295],"recall":[64,272,296],"rate":[65],"when":[66],"solving":[67],"problems":[69],"local":[71,167,250],"anomalies":[72,251],"wrapped":[74,253],"a":[75,120],"nomalies.":[76],"This":[77],"paper":[78],"presents":[79],"an":[80],"incremental":[81],"learning":[82],"model":[86],"using":[87],"density":[89],"metric":[90,139,168],"edge":[92,190],"samples.":[93],"An":[94],"isolation":[95],"region":[96,156,195],"built":[98],"by":[99,134,210],"searching":[100],"nearest":[102,110,125,131,160,182],"neighbor":[103],"each":[105],"sample.":[106],"We":[107,214],"calculate":[108],"training":[111,126,132,161,193],"point":[112,116,127,133,187,194],"test":[115,145,174,186,205],"which":[117,248],"not":[119],"global":[121,138],"anomaly":[122],"obtained":[130,209],"Euclidean":[135],"distance.":[136],"degree":[142,171],"sample":[146,175],"comes":[147,176],"from":[148,177,184],"ratio":[150,179],"radius":[153,198],"where":[157],"two":[159,212],"points":[162,206],"located.":[164],"Then,":[165],"between":[180],"distance":[183],"region.":[201],"Abnormal":[202],"scores":[203],"can":[207],"be":[208],"combining":[211],"measurements.":[213],"identify":[215],"SMART":[217],"attributes":[218,235],"that":[219],"significantly":[221],"related":[222],"failures":[225],"promote":[227],"their":[228],"weights":[229],"next":[232],"time":[233],"inputted.":[237],"experiments":[239],"carried":[241],"synthetic":[244],"public":[246,284],"datasets":[247,286],"contain":[249],"anomalies.":[254],"proposed":[256,290],"method":[257,291],"outperforms":[258],"typical":[260],"such":[263],"as":[264],"iNNE,":[265],"iForest":[266],"LOF,":[268],"achieved":[271],"rates":[273],"increase":[274],"at":[275],"most":[276],"7%.":[277],"Furthermore,":[278],"contrast":[280],"tests":[281],"also":[287],"verify":[288],"has":[292],"better":[293],"rate.":[297]},"counts_by_year":[{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}