{"id":"https://openalex.org/W3110935118","doi":"https://doi.org/10.1109/iisa50023.2020.9284346","title":"A Neural Network approach for Non-parametric Performance Assessment","display_name":"A Neural Network approach for Non-parametric Performance Assessment","publication_year":2020,"publication_date":"2020-07-15","ids":{"openalex":"https://openalex.org/W3110935118","doi":"https://doi.org/10.1109/iisa50023.2020.9284346","mag":"3110935118"},"language":"en","primary_location":{"id":"doi:10.1109/iisa50023.2020.9284346","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iisa50023.2020.9284346","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA","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/A5041603669","display_name":"Gregory Koronakos","orcid":"https://orcid.org/0000-0002-6170-3725"},"institutions":[{"id":"https://openalex.org/I154757721","display_name":"University of Piraeus","ror":"https://ror.org/02qs84g94","country_code":"GR","type":"education","lineage":["https://openalex.org/I154757721"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Gregory Koronakos","raw_affiliation_strings":["University of Piraeus,Department of Informatics,Piraeus,Greece","Department of Informatics, University of Piraeus, Piraeus, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Piraeus,Department of Informatics,Piraeus,Greece","institution_ids":["https://openalex.org/I154757721"]},{"raw_affiliation_string":"Department of Informatics, University of Piraeus, Piraeus, Greece","institution_ids":["https://openalex.org/I154757721"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006909080","display_name":"Dionisios N. Sotiropoulos","orcid":null},"institutions":[{"id":"https://openalex.org/I154757721","display_name":"University of Piraeus","ror":"https://ror.org/02qs84g94","country_code":"GR","type":"education","lineage":["https://openalex.org/I154757721"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Dionisios N. Sotiropoulos","raw_affiliation_strings":["University of Piraeus,Department of Informatics,Piraeus,Greece","Department of Informatics, University of Piraeus, Piraeus, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Piraeus,Department of Informatics,Piraeus,Greece","institution_ids":["https://openalex.org/I154757721"]},{"raw_affiliation_string":"Department of Informatics, University of Piraeus, Piraeus, Greece","institution_ids":["https://openalex.org/I154757721"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154757721"],"apc_list":null,"apc_paid":null,"fwci":0.2924,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55468322,"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":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10357","display_name":"Efficiency Analysis Using DEA","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10357","display_name":"Efficiency Analysis Using DEA","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10050","display_name":"Multi-Criteria Decision Making","score":0.9063000082969666,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/data-envelopment-analysis","display_name":"Data envelopment analysis","score":0.8511177897453308},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7534990310668945},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7040770649909973},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6332015991210938},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5501514077186584},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5240060091018677},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.45529982447624207},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.43862244486808777},{"id":"https://openalex.org/keywords/efficiency","display_name":"Efficiency","score":0.43523332476615906},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.4119843542575836},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38399678468704224},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38282641768455505},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37572839856147766},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.28891849517822266},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.14970451593399048},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12604382634162903},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11330899596214294}],"concepts":[{"id":"https://openalex.org/C22088475","wikidata":"https://www.wikidata.org/wiki/Q647974","display_name":"Data envelopment analysis","level":2,"score":0.8511177897453308},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7534990310668945},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7040770649909973},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6332015991210938},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5501514077186584},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5240060091018677},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.45529982447624207},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.43862244486808777},{"id":"https://openalex.org/C17648541","wikidata":"https://www.wikidata.org/wiki/Q2265984","display_name":"Efficiency","level":3,"score":0.43523332476615906},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.4119843542575836},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38399678468704224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38282641768455505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37572839856147766},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.28891849517822266},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.14970451593399048},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12604382634162903},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11330899596214294},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iisa50023.2020.9284346","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iisa50023.2020.9284346","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320338080","display_name":"European Social Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1533301057","https://openalex.org/W1976358775","https://openalex.org/W1977539771","https://openalex.org/W2004122973","https://openalex.org/W2005648903","https://openalex.org/W2010910568","https://openalex.org/W2048317121","https://openalex.org/W2049090015","https://openalex.org/W2060267463","https://openalex.org/W2076452041","https://openalex.org/W2081070936","https://openalex.org/W2092667551","https://openalex.org/W2128857555","https://openalex.org/W2151278668","https://openalex.org/W2158581396","https://openalex.org/W2165671206","https://openalex.org/W2901312569"],"related_works":["https://openalex.org/W2035423388","https://openalex.org/W2515668944","https://openalex.org/W312923485","https://openalex.org/W2041365066","https://openalex.org/W3123375916","https://openalex.org/W2120745168","https://openalex.org/W2096947471","https://openalex.org/W2011903341","https://openalex.org/W2529605301","https://openalex.org/W2169049974"],"abstract_inverted_index":{"Data":[0],"Envelopment":[1],"Analysis":[2],"(DEA)":[3],"is":[4,61],"the":[5,11,35,40,48,52,69,74,80,91,123,126,141],"most":[6],"popular":[7],"non-parametric":[8],"method":[9],"for":[10,72,136],"efficiency":[12,49,93,120],"assessment":[13],"of":[14,51,59,103,113,125],"homogeneous":[15],"units.":[16],"In":[17],"this":[18],"paper,":[19],"we":[20],"develop":[21],"a":[22,101],"novel":[23],"approach,":[24],"which":[25],"integrates":[26],"DEA":[27,54,60,92,128,143],"with":[28],"Artificial":[29],"Neural":[30],"Networks":[31],"(ANNs)":[32],"to":[33,46],"accelerate":[34],"evaluation":[36],"process":[37],"and":[38,111,115],"reduce":[39],"computational":[41],"burden.":[42],"We":[43,95],"employ":[44],"ANNs":[45,75,84],"estimate":[47,89],"scores":[50,121],"milestone":[53],"models.":[55,129],"The":[56,83],"relative":[57],"nature":[58],"considered":[62],"in":[63,86],"our":[64,87,97,131],"approach":[65,88,98,132],"by":[66,99],"assuring":[67],"that":[68],"DMUs":[70],"used":[71],"training":[73],"are":[76,145],"first":[77],"evaluated":[78],"against":[79],"efficient":[81],"set.":[82],"employed":[85,135],"accurately":[90],"scores.":[94],"validate":[96],"conducting":[100],"series":[102],"experiments":[104],"based":[105],"on":[106],"different":[107],"data":[108],"generation":[109],"processes":[110],"number":[112],"inputs":[114],"outputs.":[116],"Also,":[117],"these":[118],"estimated":[119],"satisfy":[122],"properties":[124],"fundamental":[127],"Thus,":[130],"can":[133],"be":[134],"large":[137],"scale":[138],"assessments":[139],"where":[140],"traditional":[142],"methods":[144],"rendered":[146],"impractical.":[147]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}