{"id":"https://openalex.org/W2891295097","doi":"https://doi.org/10.1080/24725854.2020.1774688","title":"A Bayesian framework for functional calibration of expensive computational models through non-isometric matching","display_name":"A Bayesian framework for functional calibration of expensive computational models through non-isometric matching","publication_year":2020,"publication_date":"2020-05-26","ids":{"openalex":"https://openalex.org/W2891295097","doi":"https://doi.org/10.1080/24725854.2020.1774688","mag":"2891295097"},"language":"en","primary_location":{"id":"doi:10.1080/24725854.2020.1774688","is_oa":false,"landing_page_url":"https://doi.org/10.1080/24725854.2020.1774688","pdf_url":null,"source":{"id":"https://openalex.org/S4210225672","display_name":"IISE Transactions","issn_l":"2472-5854","issn":["2472-5854","2472-5862"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IISE Transactions","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1508.01240","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Babak Farmanesh","orcid":null},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Babak Farmanesh","raw_affiliation_strings":["School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, USA","institution_ids":["https://openalex.org/I115475287"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Arash Pourhabib","orcid":"https://orcid.org/0000-0002-9394-8196"},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Arash Pourhabib","raw_affiliation_strings":["School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, USA"],"raw_orcid":"https://orcid.org/0000-0002-9394-8196","affiliations":[{"raw_affiliation_string":"School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, USA","institution_ids":["https://openalex.org/I115475287"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Balabhaskar Balasundaram","orcid":"https://orcid.org/0000-0002-3490-4257"},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Balabhaskar Balasundaram","raw_affiliation_strings":["School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, USA"],"raw_orcid":"https://orcid.org/0000-0002-3490-4257","affiliations":[{"raw_affiliation_string":"School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, USA","institution_ids":["https://openalex.org/I115475287"]}]},{"author_position":"last","author":{"id":null,"display_name":"Austin Buchanan","orcid":"https://orcid.org/0000-0003-2999-9666"},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Austin Buchanan","raw_affiliation_strings":["School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, USA"],"raw_orcid":"https://orcid.org/0000-0003-2999-9666","affiliations":[{"raw_affiliation_string":"School of Industrial Engineering and Management, Oklahoma State University, Stillwater, OK, USA","institution_ids":["https://openalex.org/I115475287"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I115475287"],"apc_list":null,"apc_paid":null,"fwci":0.9512,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.80288956,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"53","issue":"3","first_page":"352","last_page":"364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.5446000099182129,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.5446000099182129,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.05990000069141388,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.04360000044107437,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/identifiability","display_name":"Identifiability","score":0.8040000200271606},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.7364000082015991},{"id":"https://openalex.org/keywords/unobservable","display_name":"Unobservable","score":0.678600013256073},{"id":"https://openalex.org/keywords/computational-model","display_name":"Computational model","score":0.5670999884605408},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5512999892234802},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5336999893188477},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5235999822616577},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5174999833106995},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.453000009059906}],"concepts":[{"id":"https://openalex.org/C122770356","wikidata":"https://www.wikidata.org/wiki/Q1656753","display_name":"Identifiability","level":2,"score":0.8040000200271606},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7364000082015991},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.678600013256073},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6297000050544739},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.5670999884605408},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5512999892234802},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5349000096321106},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5336999893188477},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5235999822616577},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5174999833106995},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.453000009059906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4372999966144562},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42239999771118164},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.39570000767707825},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3903000056743622},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3450999855995178},{"id":"https://openalex.org/C127964446","wikidata":"https://www.wikidata.org/wiki/Q1092142","display_name":"Computational resource","level":3,"score":0.33880001306533813},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31709998846054077},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.31610000133514404},{"id":"https://openalex.org/C32848918","wikidata":"https://www.wikidata.org/wiki/Q845789","display_name":"Observable","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29750001430511475},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2822999954223633},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.27459999918937683},{"id":"https://openalex.org/C176222170","wikidata":"https://www.wikidata.org/wiki/Q5157340","display_name":"Computational statistics","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.25440001487731934}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/24725854.2020.1774688","is_oa":false,"landing_page_url":"https://doi.org/10.1080/24725854.2020.1774688","pdf_url":null,"source":{"id":"https://openalex.org/S4210225672","display_name":"IISE Transactions","issn_l":"2472-5854","issn":["2472-5854","2472-5862"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IISE Transactions","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1508.01240","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1508.01240","pdf_url":"https://arxiv.org/pdf/1508.01240","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"pmh:oai:RePEc:taf:uiiexx:v:53:y:2020:i:3:p:352-364","is_oa":false,"landing_page_url":"http://hdl.handle.net/10.1080/24725854.2020.1774688","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"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":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1508.01240","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1508.01240","pdf_url":"https://arxiv.org/pdf/1508.01240","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5960717788","display_name":null,"funder_award_id":"1662757","funder_id":"https://openalex.org/F4320337391","funder_display_name":"Division of Civil, Mechanical and Manufacturing Innovation"}],"funders":[{"id":"https://openalex.org/F4320337391","display_name":"Division of Civil, Mechanical and Manufacturing Innovation","ror":"https://ror.org/028yd4c30"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W34339474","https://openalex.org/W1502922572","https://openalex.org/W1540155273","https://openalex.org/W1709036216","https://openalex.org/W1973333099","https://openalex.org/W1992870395","https://openalex.org/W2007101062","https://openalex.org/W2026170388","https://openalex.org/W2027319489","https://openalex.org/W2032789430","https://openalex.org/W2051530843","https://openalex.org/W2067278522","https://openalex.org/W2073401015","https://openalex.org/W2077405310","https://openalex.org/W2078336410","https://openalex.org/W2078454401","https://openalex.org/W2082161089","https://openalex.org/W2092612581","https://openalex.org/W2103889133","https://openalex.org/W2110105948","https://openalex.org/W2127739279","https://openalex.org/W2130472914","https://openalex.org/W2144963188","https://openalex.org/W2166164984","https://openalex.org/W2180772693","https://openalex.org/W2227557434","https://openalex.org/W2510654329","https://openalex.org/W2755155569","https://openalex.org/W2807456963","https://openalex.org/W2963045461","https://openalex.org/W2964037800","https://openalex.org/W4213283575"],"related_works":[],"abstract_inverted_index":{"We":[0,22,80],"study":[1],"statistical":[2],"calibration,":[3,26],"i.e.,":[4],"adjusting":[5],"features":[6],"of":[7,43,67,90,99,143,155,174],"a":[8,41,64,96,103,117,140],"computational":[9,55,92,104,114],"model":[10,105,115],"that":[11,54,87,171],"are":[12,40,57,77,123],"not":[13,78],"observable":[14],"or":[15,179],"controllable":[16],"in":[17,29,50,125,172],"its":[18,107],"associated":[19,108],"physical":[20,109],"system.":[21,110],"focus":[23],"on":[24],"functional":[25],"which":[27,149],"arises":[28],"many":[30,51],"manufacturing":[31],"processes":[32],"where":[33],"the":[34,44,74,113,126,131,136],"unobservable":[35],"features,":[36],"called":[37],"calibration":[38,75,89,127,137,185],"variables,":[39],"function":[42],"input":[45],"variables.":[46],"A":[47],"major":[48],"challenge":[49],"applications":[52],"is":[53,180],"models":[56,93],"expensive":[58,91],"and":[59,106],"can":[60],"only":[61,95],"be":[62],"evaluated":[63],"limited":[65,97],"number":[66,98],"times.":[68],"Furthermore,":[69],"without":[70],"making":[71],"strong":[72],"assumptions,":[73],"variables":[76],"identifiable.":[79],"propose":[81],"Bayesian":[82],"Non-isometric":[83],"Matching":[84],"Calibration":[85],"(BNMC)":[86],"allows":[88],"with":[94,116],"samples":[100],"taken":[101],"from":[102,139],"BNMC":[111,177],"replaces":[112],"dynamic":[118],"Gaussian":[119],"process":[120],"whose":[121],"parameters":[122],"trained":[124],"procedure.":[128],"To":[129],"resolve":[130],"identifiability":[132],"issue,":[133],"we":[134],"present":[135],"problem":[138],"geometric":[141],"perspective":[142],"non-isometric":[144],"curve":[145],"to":[146,152,159],"surface":[147],"matching,":[148],"enables":[150],"us":[151],"take":[153],"advantage":[154],"combinatorial":[156],"optimization":[157],"techniques":[158],"extract":[160],"necessary":[161],"information":[162],"for":[163],"constructing":[164],"prior":[165],"distributions.":[166],"Our":[167],"numerical":[168],"experiments":[169],"demonstrate":[170],"terms":[173],"prediction":[175],"accuracy":[176],"outperforms,":[178],"comparable":[181],"to,":[182],"other":[183],"existing":[184],"frameworks.":[186]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2018-09-27T00:00:00"}