{"id":"https://openalex.org/W4385076196","doi":"https://doi.org/10.1016/j.ijar.2023.108988","title":"Physics-informed learning under epistemic uncertainty with an application to system health modeling","display_name":"Physics-informed learning under epistemic uncertainty with an application to system health modeling","publication_year":2023,"publication_date":"2023-07-22","ids":{"openalex":"https://openalex.org/W4385076196","doi":"https://doi.org/10.1016/j.ijar.2023.108988"},"language":"en","primary_location":{"id":"doi:10.1016/j.ijar.2023.108988","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijar.2023.108988","pdf_url":null,"source":{"id":"https://openalex.org/S33368595","display_name":"International Journal of Approximate Reasoning","issn_l":"0888-613X","issn":["0888-613X","1873-4731"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Approximate Reasoning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.ijar.2023.108988","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007997944","display_name":"Luciano S\u00e1nchez","orcid":"https://orcid.org/0000-0002-2446-1915"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Luciano S\u00e1nchez","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088736154","display_name":"Nahuel Costa","orcid":"https://orcid.org/0000-0002-9189-2192"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nahuel Costa","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014275379","display_name":"Jos\u00e9 Otero","orcid":"https://orcid.org/0000-0002-5974-0893"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jos\u00e9 Otero","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5070267406","display_name":"In\u00e9s Couso","orcid":"https://orcid.org/0000-0002-1675-6203"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"In\u00e9s Couso","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5007997944"],"corresponding_institution_ids":[],"apc_list":{"value":2960,"currency":"USD","value_usd":2960},"apc_paid":{"value":2960,"currency":"USD","value_usd":2960},"fwci":2.3364,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.89268518,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"161","issue":null,"first_page":"108988","last_page":"108988"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9991000294685364,"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":0.9991000294685364,"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10968","display_name":"Statistical Distribution Estimation and Applications","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/regret","display_name":"Regret","score":0.7770265340805054},{"id":"https://openalex.org/keywords/physical-system","display_name":"Physical system","score":0.7092164158821106},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6420612335205078},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5419431924819946},{"id":"https://openalex.org/keywords/partial-differential-equation","display_name":"Partial differential equation","score":0.4179726541042328},{"id":"https://openalex.org/keywords/complex-system","display_name":"Complex system","score":0.4128195643424988},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37356042861938477},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36017757654190063},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3009802997112274},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15939420461654663}],"concepts":[{"id":"https://openalex.org/C50817715","wikidata":"https://www.wikidata.org/wiki/Q79895177","display_name":"Regret","level":2,"score":0.7770265340805054},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.7092164158821106},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6420612335205078},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5419431924819946},{"id":"https://openalex.org/C93779851","wikidata":"https://www.wikidata.org/wiki/Q271977","display_name":"Partial differential equation","level":2,"score":0.4179726541042328},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.4128195643424988},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37356042861938477},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36017757654190063},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3009802997112274},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15939420461654663},{"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.ijar.2023.108988","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijar.2023.108988","pdf_url":null,"source":{"id":"https://openalex.org/S33368595","display_name":"International Journal of Approximate Reasoning","issn_l":"0888-613X","issn":["0888-613X","1873-4731"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Approximate Reasoning","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.ijar.2023.108988","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijar.2023.108988","pdf_url":null,"source":{"id":"https://openalex.org/S33368595","display_name":"International Journal of Approximate Reasoning","issn_l":"0888-613X","issn":["0888-613X","1873-4731"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Approximate Reasoning","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1969394306","https://openalex.org/W1993489996","https://openalex.org/W2000301175","https://openalex.org/W2003359560","https://openalex.org/W2055873761","https://openalex.org/W2124409483","https://openalex.org/W2516153342","https://openalex.org/W2810873527","https://openalex.org/W2902700103","https://openalex.org/W3001566134","https://openalex.org/W3012258764","https://openalex.org/W3127209452","https://openalex.org/W3163993681","https://openalex.org/W3205865221","https://openalex.org/W3205961258","https://openalex.org/W3216253091","https://openalex.org/W4212940123","https://openalex.org/W4214484890","https://openalex.org/W4221142064","https://openalex.org/W4235646257","https://openalex.org/W4245812996","https://openalex.org/W4246840991","https://openalex.org/W4255362326","https://openalex.org/W4294484493","https://openalex.org/W4298216306","https://openalex.org/W4301860527","https://openalex.org/W4308033457","https://openalex.org/W4315628777","https://openalex.org/W4318481641","https://openalex.org/W4321767449","https://openalex.org/W4367857187","https://openalex.org/W6678281827","https://openalex.org/W6742671534","https://openalex.org/W6809502644"],"related_works":["https://openalex.org/W2971351794","https://openalex.org/W4376155396","https://openalex.org/W1947085858","https://openalex.org/W2101991911","https://openalex.org/W2174986909","https://openalex.org/W2527791220","https://openalex.org/W2155070487","https://openalex.org/W4311589891","https://openalex.org/W3123835761","https://openalex.org/W2018375047"],"abstract_inverted_index":{"This":[0],"study":[1],"proposes":[2],"a":[3,15,31,47,86,185],"methodology":[4],"for":[5],"developing":[6],"deterioration":[7,167],"models":[8],"to":[9,45,78,102,111,117,160],"estimate":[10],"the":[11,28,43,52,57,62,71,79,93,98,105,125,129,151,162,166,172,177,194],"remaining":[12],"lifetime":[13],"of":[14,23,33,49,56,59,61,67,70,88,97,121,128,131,145,165,176,184],"system":[16,29,72],"using":[17],"physics-informed":[18],"learning.":[19],"The":[20,64,81,174],"approach":[21],"consists":[22,66],"combining":[24],"physical":[25,82,106,136],"knowledge":[26,83,137],"about":[27],"with":[30],"set":[32,48,87],"data":[34,65],"obtained":[35],"from":[36,75,134],"similar":[37],"systems":[38],"that":[39,91,169],"have":[40],"failed":[41],"in":[42,189,196],"past":[44],"build":[46],"constraints":[50],"on":[51,124,201],"evolution":[53,127,164],"over":[54],"time":[55,163],"state":[58,130],"health":[60,132],"system.":[63,99],"partial":[68],"measurements":[69],"variables,":[73],"taken":[74],"its":[76,141],"commissioning":[77],"present.":[80],"used":[84],"comprises":[85],"differential":[89],"equations":[90],"approximate":[92],"dynamics":[94],"and":[95,143,154,193],"ageing":[96],"In":[100,148],"contrast":[101],"other":[103],"studies,":[104],"model":[107],"is":[108,115,180],"not":[109],"assumed":[110],"be":[112,118],"accurate,":[113],"but":[114],"considered":[116],"an":[119],"approximation":[120],"reality.":[122],"Constraints":[123],"temporal":[126],"derived":[133],"this":[135,149],"take":[138],"into":[139],"account":[140],"imprecision":[142],"consist":[144],"possibility":[146],"distributions.":[147],"study,":[150],"max-max,":[152],"max-min":[153],"min-max":[155],"regret":[156],"principles":[157],"are":[158,205],"applied":[159],"extract":[161],"rate":[168],"best":[170],"fits":[171],"constraints.":[173],"effectiveness":[175],"proposed":[178],"algorithm":[179],"evaluated":[181],"by":[182],"means":[183],"comparative":[186],"empirical":[187],"analysis":[188],"different":[190],"use":[191],"cases,":[192],"situations":[195],"which":[197],"informed":[198],"learning":[199],"improves":[200],"purely":[202],"data-driven":[203],"algorithms":[204],"analysed.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}
