{"id":"https://openalex.org/W3011013547","doi":"https://doi.org/10.1109/ccwc47524.2020.9031232","title":"AIOPS Prediction for Hard Drive Failures Based on Stacking Ensemble Model","display_name":"AIOPS Prediction for Hard Drive Failures Based on Stacking Ensemble Model","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3011013547","doi":"https://doi.org/10.1109/ccwc47524.2020.9031232","mag":"3011013547"},"language":"en","primary_location":{"id":"doi:10.1109/ccwc47524.2020.9031232","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc47524.2020.9031232","pdf_url":null,"source":{"id":"https://openalex.org/S4306498584","display_name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"},"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":"https://openalex.org/A5100386385","display_name":"Haifeng Wang","orcid":"https://orcid.org/0000-0001-5381-1657"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]},{"id":"https://openalex.org/I4210123971","display_name":"Kensington Health","ror":"https://ror.org/02qcscp23","country_code":"CA","type":"nonprofit","lineage":["https://openalex.org/I4210123971"]}],"countries":["CA","US"],"is_corresponding":false,"raw_author_name":"Haifeng Wang","raw_affiliation_strings":["Penn State New Kensington, Penn State University, New kensington, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Penn State New Kensington, Penn State University, New kensington, US","institution_ids":["https://openalex.org/I130769515","https://openalex.org/I4210123971"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101949480","display_name":"Haili Zhang","orcid":"https://orcid.org/0000-0003-3994-7181"},"institutions":[{"id":"https://openalex.org/I4210144143","display_name":"Inspur (China)","ror":"https://ror.org/0474p4r72","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210144143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haili Zhang","raw_affiliation_strings":["Inspur Storage Department, Inspur, Jinan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Inspur Storage Department, Inspur, Jinan, China","institution_ids":["https://openalex.org/I4210144143"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"0417","last_page":"0423"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11181","display_name":"Advanced Data Storage Technologies","score":0.9952999949455261,"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.9952999949455261,"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/T10101","display_name":"Cloud Computing and Resource Management","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11614","display_name":"Cloud Data Security Solutions","score":0.9787999987602234,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8005589246749878},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.6871166229248047},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5887773633003235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5764956474304199},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5686008334159851},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5647464990615845},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5347750186920166},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.524055004119873},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5237486362457275},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5196924805641174},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.49106574058532715},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47445568442344666},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4158884286880493},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.1257202923297882}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8005589246749878},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.6871166229248047},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5887773633003235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5764956474304199},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5686008334159851},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5647464990615845},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5347750186920166},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.524055004119873},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5237486362457275},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5196924805641174},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.49106574058532715},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47445568442344666},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4158884286880493},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.1257202923297882},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"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/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccwc47524.2020.9031232","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc47524.2020.9031232","pdf_url":null,"source":{"id":"https://openalex.org/S4306498584","display_name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 10th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1994493193","https://openalex.org/W2267642256","https://openalex.org/W2509298940","https://openalex.org/W2565047864","https://openalex.org/W2740127658","https://openalex.org/W2757703774","https://openalex.org/W2784247142","https://openalex.org/W2884664388","https://openalex.org/W2895690683","https://openalex.org/W2902653840","https://openalex.org/W2944703101","https://openalex.org/W2970119753","https://openalex.org/W3099861110","https://openalex.org/W3102570742","https://openalex.org/W4236586490","https://openalex.org/W6741898950","https://openalex.org/W6753749979","https://openalex.org/W7037320950"],"related_works":["https://openalex.org/W2794896638","https://openalex.org/W2891633941","https://openalex.org/W1807784185","https://openalex.org/W4390905871","https://openalex.org/W3202800081","https://openalex.org/W1909207154","https://openalex.org/W3124390867","https://openalex.org/W3101614107","https://openalex.org/W1514365828","https://openalex.org/W4390971112"],"abstract_inverted_index":{"This":[0],"paper":[1],"mainly":[2],"shares":[3],"a":[4,17,70,98,108,142],"successful":[5],"Artificial":[6],"Intelligence":[7],"for":[8,16,63],"IT":[9],"Operations":[10],"(AIOps)":[11],"solution":[12],"we":[13,34,55,68,91,121],"have":[14],"built":[15],"cloud":[18],"storage":[19],"array":[20],"to":[21,40,80,101,179,183],"deal":[22],"with":[23,97],"unbalanced":[24,37,119],"hard":[25],"disk":[26,31,38,64,171,176],"failure":[27,65,172],"data":[28,39],"and":[29,51,76,134,152,173,186],"predict":[30,169],"failure.":[32],"Firstly,":[33],"preprocessed":[35],"the":[36,93,103,118,124,161,170],"filter":[41],"out":[42],"irrelevant":[43],"raw":[44],"data.":[45],"Based":[46],"on":[47,117],"SMART":[48],"(Self-Monitoring,":[49],"Analysis,":[50],"Reporting":[52],"Technology)":[53],"attributes,":[54],"extracted":[56],"14":[57,180,182],"preliminary":[58],"attributes":[59],"as":[60,137],"training":[61],"features":[62,139],"prediction.":[66],"Secondly,":[67],"used":[69,92],"feature":[71],"extraction":[72,78],"library":[73],"called":[74],"Tsfresh":[75],"16":[77],"methods":[79],"regenerate":[81],"more":[82,150,187],"than":[83],"1500":[84],"features.":[85,106],"To":[86],"accelerate":[87],"machine":[88],"learning":[89,145,165],"process,":[90],"Benjamini":[94],"Yekutieli":[95],"procedure":[96],"significance":[99],"test":[100],"select":[102],"most":[104],"relevant":[105],"Since":[107],"single":[109],"predictive":[110],"model":[111,146,166],"no":[112],"longer":[113],"performs":[114],"sufficiently":[115],"well":[116],"dataset,":[120],"finally":[122],"input":[123,140],"prediction":[125,154],"results":[126,158],"calculated":[127],"by":[128],"three":[129],"algorithms(XGBoost":[130],"classification,":[131,133],"LSTM":[132],"XGBoost":[135],"regression)":[136],"new":[138],"of":[141,175],"stacking":[143,163],"ensemble":[144,164],"that":[147,160],"can":[148,167],"generate":[149],"stable":[151],"accurate":[153],"results.":[155],"The":[156],"experimental":[157],"showed":[159],"proposed":[162],"accurately":[168],"necessity":[174],"replacement":[177],"0":[178],"days,":[181],"42":[184],"days":[185,188],"in":[189],"advance.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
