{"id":"https://openalex.org/W3216269637","doi":"https://doi.org/10.1109/mascots53633.2021.9614298","title":"Deep Learning Models for Automated Identification of Scheduling Policies","display_name":"Deep Learning Models for Automated Identification of Scheduling Policies","publication_year":2021,"publication_date":"2021-11-03","ids":{"openalex":"https://openalex.org/W3216269637","doi":"https://doi.org/10.1109/mascots53633.2021.9614298","mag":"3216269637"},"language":"en","primary_location":{"id":"doi:10.1109/mascots53633.2021.9614298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mascots53633.2021.9614298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 29th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","raw_type":"proceedings-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/A5046386928","display_name":"Yichong Chen","orcid":"https://orcid.org/0000-0002-2522-3839"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Yichong Chen","raw_affiliation_strings":["Imperial College, London, UK"],"affiliations":[{"raw_affiliation_string":"Imperial College, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045967404","display_name":"Giuliano Casale","orcid":"https://orcid.org/0000-0003-4548-7951"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Giuliano Casale","raw_affiliation_strings":["Imperial College, London, UK"],"affiliations":[{"raw_affiliation_string":"Imperial College, London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5046386928"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.6433,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75410233,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9817000031471252,"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"}},"topics":[{"id":"https://openalex.org/T10703","display_name":"Business Process Modeling and Analysis","score":0.9817000031471252,"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"}},{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9771000146865845,"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/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.9735999703407288,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.75133216381073},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5754132866859436},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5590011477470398},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5483551025390625},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5008294582366943},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3782011568546295},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11919572949409485}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.75133216381073},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5754132866859436},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5590011477470398},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5483551025390625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5008294582366943},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3782011568546295},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11919572949409485},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mascots53633.2021.9614298","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mascots53633.2021.9614298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 29th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","raw_type":"proceedings-article"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/92165","is_oa":false,"landing_page_url":"http://hdl.handle.net/10044/1/92165","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2021 29th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1459540712","https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W2001684753","https://openalex.org/W2062259223","https://openalex.org/W2064675550","https://openalex.org/W2094055697","https://openalex.org/W2119242743","https://openalex.org/W2155524176","https://openalex.org/W2194775991","https://openalex.org/W2313373593","https://openalex.org/W2342179536","https://openalex.org/W2587689879","https://openalex.org/W2896457183","https://openalex.org/W2963542740","https://openalex.org/W3007715160","https://openalex.org/W3010541414","https://openalex.org/W3100509614","https://openalex.org/W3147878797","https://openalex.org/W4212922449","https://openalex.org/W4239510810","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6687483927","https://openalex.org/W6739901393","https://openalex.org/W6755207826","https://openalex.org/W6785344259"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W2961085424","https://openalex.org/W3215138031","https://openalex.org/W4306674287","https://openalex.org/W4321369474","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3046775127","https://openalex.org/W3082895349"],"abstract_inverted_index":{"Queueing":[0],"network":[1,124],"models":[2,8,97],"are":[3,71],"commonly":[4],"used":[5],"as":[6,25,85],"performance":[7,82],"of":[9,81,110,121,137],"distributed":[10],"software":[11],"applications":[12],"and":[13,48,78,153],"service-based":[14],"systems.":[15],"Although":[16],"several":[17],"methods":[18,111],"exist":[19],"for":[20,67,74,112],"learning":[21,92],"their":[22,49,62],"parameters,":[23],"such":[24,84],"demand":[26],"estimation":[27],"methods,":[28],"little":[29],"research":[30],"has":[31],"been":[32],"carried":[33],"out":[34],"in":[35,59,102,140],"the":[36,55,108,122,134,138,147],"literature":[37],"on":[38,54,95],"automatically":[39],"identifying":[40],"scheduling":[41,135],"policies":[42,47],"from":[43],"empirical":[44],"datasets.":[45],"Scheduling":[46],"parameters":[50],"have":[51],"an":[52,127],"impact":[53],"model\u2019s":[56],"stationary":[57],"distribution":[58],"general,":[60],"thus":[61],"correct":[63],"determination":[64],"is":[65],"important":[66],"model":[68,149],"accuracy.":[69],"They":[70],"particularly":[72],"relevant":[73],"correctly":[75],"estimating":[76],"percentiles":[77],"higher-order":[79],"moments":[80],"indexes":[83],"response":[86],"times.":[87],"We":[88,144],"propose":[89],"a":[90,99,118,141],"deep":[91],"technique":[93,101],"based":[94],"transformer":[96,148],"-":[98],"common":[100],"natural":[103],"language":[104],"processing,":[105],"to":[106],"address":[107],"lack":[109],"this":[113],"parameter":[114],"identification":[115],"problem.":[116],"From":[117],"sample":[119],"path":[120],"joint":[123],"state,":[125],"or":[126,161],"aggregate":[128],"thereof,":[129],"our":[130],"approach":[131],"can":[132],"classify":[133],"policy":[136],"stations":[139],"queueing":[142],"network.":[143],"show":[145],"that":[146],"delivers":[150],"good-classification":[151],"precision":[152],"recall,":[154],"improving":[155],"significantly":[156],"over":[157],"support":[158],"vector":[159],"machines":[160],"simpler":[162],"recurrent":[163],"neural":[164],"networks.":[165]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}
