{"id":"https://openalex.org/W2909765308","doi":"https://doi.org/10.2514/6.2019-1490","title":"A Nonparametric-based Approach for the Characterization and Propagation of Epistemic Uncertainty due to Small Datasets","display_name":"A Nonparametric-based Approach for the Characterization and Propagation of Epistemic Uncertainty due to Small Datasets","publication_year":2019,"publication_date":"2019-01-06","ids":{"openalex":"https://openalex.org/W2909765308","doi":"https://doi.org/10.2514/6.2019-1490","mag":"2909765308"},"language":"en","primary_location":{"id":"doi:10.2514/6.2019-1490","doi":"https://doi.org/10.2514/6.2019-1490","is_oa":false,"landing_page_url":"https://doi.org/10.2514/6.2019-1490","pdf_url":null,"source":{"id":"https://openalex.org/S4363604158","display_name":"AIAA SciTech Forum","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"AIAA Scitech 2019 Forum","raw_type":"proceedings-article"},"volume":null,"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/A5048488745","display_name":"Zhenyu Gao","orcid":"https://orcid.org/0000-0002-8177-7123","observed_orcids":["https://orcid.org/0000-0002-8177-7123","https://orcid.org/0000-0001-9456-8059"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhenyu Gao","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045189315","display_name":"Dongwook Lim","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongwook Lim","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053336274","display_name":"Katherine G. Schwartz","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Katherine G. Schwartz","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044421630","display_name":"Dimitri N. Mavris","orcid":"https://orcid.org/0000-0001-8783-4988","observed_orcids":["https://orcid.org/0000-0001-8783-4988"]},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dimitri N. Mavris","raw_affiliation_strings":["Georgia Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":3.1689,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.89936102,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T11357","display_name":"Risk and Safety Analysis","score":0.0019000000320374966,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T11890","display_name":"Scientific Measurement and Uncertainty Evaluation","score":0.0012000000569969416,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/epistemic-uncertainty","display_name":"epistemic uncertainty","score":0.996999979019165},{"id":"https://openalex.org/keywords/error-propagation","display_name":"error propagation","score":0.9440000057220459},{"id":"https://openalex.org/keywords/small-datasets","display_name":"small datasets","score":0.8980000019073486},{"id":"https://openalex.org/keywords/nonparametric-density-estimation","display_name":"nonparametric density estimation","score":0.75},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"kernel density estimation","score":1.0},{"id":"https://openalex.org/keywords/bootstrap-method","display_name":"bootstrapping","score":0.8939999938011169},{"id":"https://openalex.org/keywords/copulas","display_name":"copulas","score":0.7730000019073486},{"id":"https://openalex.org/keywords/inversion-method","display_name":"inverse method","score":0.7730000019073486},{"id":"https://openalex.org/keywords/dependence-structure","display_name":"dependence structure","score":0.9259999990463257}],"concepts":[{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.6416083574295044},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.6412457823753357},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.6253628134727478},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.587579607963562},{"id":"https://openalex.org/C123614077","wikidata":"https://www.wikidata.org/wiki/Q1364905","display_name":"Propagation of uncertainty","level":2,"score":0.5510216951370239},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.4996500015258789},{"id":"https://openalex.org/C177803969","wikidata":"https://www.wikidata.org/wiki/Q29205","display_name":"Uncertainty analysis","level":2,"score":0.4142796993255615},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34832340478897095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34126555919647217},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34077906608581543},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.33901911973953247},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3333016633987427},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23085185885429382},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2110845446586609},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17929509282112122},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.07318717241287231},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.06914973258972168},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.2514/6.2019-1490","doi":"https://doi.org/10.2514/6.2019-1490","is_oa":false,"landing_page_url":"https://doi.org/10.2514/6.2019-1490","pdf_url":null,"source":{"id":"https://openalex.org/S4363604158","display_name":"AIAA SciTech Forum","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"AIAA Scitech 2019 Forum","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-141162","doi":null,"is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-141162","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W609662346","https://openalex.org/W629338568","https://openalex.org/W651705667","https://openalex.org/W1492815834","https://openalex.org/W1549245336","https://openalex.org/W1607663648","https://openalex.org/W1973767001","https://openalex.org/W1981832299","https://openalex.org/W1989569109","https://openalex.org/W1996908140","https://openalex.org/W1998378660","https://openalex.org/W2032558547","https://openalex.org/W2039812482","https://openalex.org/W2046577380","https://openalex.org/W2051195364","https://openalex.org/W2052524623","https://openalex.org/W2072740983","https://openalex.org/W2076205463","https://openalex.org/W2091230023","https://openalex.org/W2111959010","https://openalex.org/W2117897510","https://openalex.org/W2119587361","https://openalex.org/W2150104128","https://openalex.org/W2158196600","https://openalex.org/W2579850834","https://openalex.org/W2604311173","https://openalex.org/W2616683510","https://openalex.org/W2751964841","https://openalex.org/W2766821428","https://openalex.org/W2773804690","https://openalex.org/W2788201955","https://openalex.org/W2811339906","https://openalex.org/W4233014035","https://openalex.org/W4247096189","https://openalex.org/W4252979015"],"related_works":["https://openalex.org/W2805711383","https://openalex.org/W2616683510","https://openalex.org/W2319508313","https://openalex.org/W2102883552","https://openalex.org/W2046577380","https://openalex.org/W1991452580","https://openalex.org/W2784741090","https://openalex.org/W2065638573","https://openalex.org/W2170798819","https://openalex.org/W2162517559"],"abstract_inverted_index":{"Quantification":[0],"of":[1,9,25,41,72,79,85,91,102,111,127,170],"uncertainty":[2,42,46,74,117,139,171],"is":[3,16,141,180],"ideally":[4],"performed":[5],"by":[6,173,182],"the":[7,37,68,77,89,124,128,147,158,166],"use":[8,90],"highly":[10],"precise":[11],"and":[12,51,56,70,96,131,138,151,185],"consistent":[13],"information,":[14],"which":[15],"rarely":[17],"available":[18,34],"in":[19,143,189],"many":[20],"applications":[21],"due":[22,75],"to":[23,48,65,76,98,156,164],"lack":[24,78],"knowledge":[26],"and/or":[27],"resources.":[28],"When":[29],"only":[30],"small":[31,107,144],"datasets":[32],"are":[33,114,154],"for":[35,116],"characterizing":[36],"underlying":[38],"probability":[39,100],"distributions":[40,101],"sources,":[43],"related":[44],"epistemic":[45,73],"needs":[47],"be":[49],"characterized":[50],"propagated":[52],"with":[53],"weaker":[54],"assumptions":[55],"greater":[57],"flexibility.":[58],"This":[59],"paper":[60,87],"proposes":[61],"a":[62,132,186],"nonparametric-based":[63],"approach":[64],"further":[66],"facilitate":[67],"characterization":[69],"propagation":[71],"sufficient":[80],"data.":[81],"The":[82,177],"first":[83],"part":[84],"this":[86],"presents":[88],"Kernel":[92],"Density":[93],"Estimation":[94],"(KDE)":[95],"Bootstrap":[97],"estimate":[99,122,126,135],"random":[103,162],"variables":[104],"based":[105],"on":[106],"datasets.":[108,145],"Two":[109],"types":[110],"density":[112,121,134],"estimates":[113],"provided":[115],"propagation:":[118],"an":[119],"optimal":[120],"representing":[123,136],"best":[125],"true":[129],"distribution,":[130],"conservative":[133],"risk":[137],"that":[140],"inherent":[142],"In":[146],"second":[148],"part,":[149],"copulas":[150],"inversion":[152],"method":[153,179],"applied":[155],"model":[157],"dependence":[159],"structure":[160],"among":[161],"variables,":[163],"mitigate":[165],"overestimation":[167],"or":[168],"underestimation":[169],"caused":[172],"incorrect":[174],"independence":[175],"assumption.":[176],"proposed":[178],"illustrated":[181],"various":[183],"illustrations":[184],"challenging":[187],"problem":[188],"aviation":[190],"environmental":[191],"impact":[192],"analysis.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2019-01-25T00:00:00"}
