{"id":"https://openalex.org/W3198698606","doi":"https://doi.org/10.1145/3468891.3468909","title":"Deep Neural Network Based Application Capacity Analysis in Finance System","display_name":"Deep Neural Network Based Application Capacity Analysis in Finance System","publication_year":2021,"publication_date":"2021-04-23","ids":{"openalex":"https://openalex.org/W3198698606","doi":"https://doi.org/10.1145/3468891.3468909","mag":"3198698606"},"language":"en","primary_location":{"id":"doi:10.1145/3468891.3468909","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3468891.3468909","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 6th International Conference on Machine Learning Technologies","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/A5022716964","display_name":"Liang Zong","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Liang Zong","raw_affiliation_strings":["Standard Chartered Global Business Services Co.,Ltd, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Standard Chartered Global Business Services Co.,Ltd, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5022716964"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2713,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.4107179,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"122","last_page":"126"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9958000183105469,"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":0.9958000183105469,"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":0.994700014591217,"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/T11891","display_name":"Big Data and Business Intelligence","score":0.9427000284194946,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.8666245937347412},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7638028860092163},{"id":"https://openalex.org/keywords/capacity-planning","display_name":"Capacity planning","score":0.5953937768936157},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5806267857551575},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5462082028388977},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5269409418106079},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5039939284324646},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.4778560996055603},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.47638148069381714},{"id":"https://openalex.org/keywords/plan","display_name":"Plan (archaeology)","score":0.45749813318252563},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32134416699409485}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8666245937347412},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7638028860092163},{"id":"https://openalex.org/C2781007418","wikidata":"https://www.wikidata.org/wiki/Q1456934","display_name":"Capacity planning","level":2,"score":0.5953937768936157},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5806267857551575},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5462082028388977},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5269409418106079},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5039939284324646},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.4778560996055603},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.47638148069381714},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.45749813318252563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32134416699409485},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3468891.3468909","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3468891.3468909","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 6th International Conference on Machine Learning Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2046183884","https://openalex.org/W2070317073","https://openalex.org/W2076063813","https://openalex.org/W2089126265","https://openalex.org/W2109239225","https://openalex.org/W2429298957","https://openalex.org/W2578279218","https://openalex.org/W2775287056","https://openalex.org/W2894393199","https://openalex.org/W4231109964","https://openalex.org/W4286447321","https://openalex.org/W6747761800"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W4382618745","https://openalex.org/W2159197444","https://openalex.org/W2393489561","https://openalex.org/W2162309336","https://openalex.org/W3149898195"],"abstract_inverted_index":{"The":[0,23,123],"goal":[1],"of":[2],"system":[3,33,68],"capacity":[4,11,16,25,71],"analysis":[5,26],"is":[6,27,73,105],"to":[7,30,65,88,145],"understand":[8],"the":[9,28,32,67,84],"current":[10],"usage":[12],"and":[13,35,50,60],"forecast":[14],"future":[15],"impact":[17],"based":[18,100],"on":[19],"various":[20],"business":[21],"scenarios.":[22],"successful":[24],"key":[29],"identify":[31],"bottleneck":[34],"plan":[36],"for":[37,44,108],"better":[38,132],"resource":[39],"allocation.":[40],"However,":[41],"IT":[42],"systems":[43],"finance":[45,110,150],"company":[46],"are":[47],"inherently":[48],"large":[49],"complex":[51,109],"with":[52,55,135],"numerous":[53],"interfaces":[54],"other":[56,139],"systems.":[57,111],"Thus,":[58],"identifying":[59],"selecting":[61],"a":[62,131],"good":[63],"model":[64,128],"describe":[66],"interdependence":[69],"from":[70],"perspective":[72],"important":[74],"but":[75],"challenging":[76],"problem.":[77],"In":[78],"our":[79,121,126,142],"paper,":[80],"we":[81,86,97],"first":[82],"define":[83],"problem":[85,147],"want":[87],"solve.":[89],"We":[90,112],"discuss":[91],"2":[92],"approaches":[93],"as":[94,120],"baselines.":[95],"Then":[96],"propose":[98],"DNN":[99],"multiple":[101],"linear":[102],"regression,":[103],"which":[104],"more":[106],"efficient":[107],"collected":[113],"12":[114],"months":[115],"real":[116,149],"production":[117],"volume":[118],"data":[119],"dataset.":[122],"experiment":[124],"shows":[125],"proposed":[127],"can":[129],"give":[130],"performance":[133],"compared":[134],"baseline":[136],"approaches.":[137],"Unlike":[138],"research":[140],"papers,":[141],"proposal":[143],"focuses":[144],"solve":[146],"in":[148],"industry.":[151]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
