{"id":"https://openalex.org/W4388320640","doi":"https://doi.org/10.1145/3600100.3626268","title":"Dynamic Bayesian Networks for Fault Prognosis","display_name":"Dynamic Bayesian Networks for Fault Prognosis","publication_year":2023,"publication_date":"2023-11-03","ids":{"openalex":"https://openalex.org/W4388320640","doi":"https://doi.org/10.1145/3600100.3626268"},"language":"en","primary_location":{"id":"doi:10.1145/3600100.3626268","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3600100.3626268","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","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/A5009233055","display_name":"Ojas Pradhan","orcid":"https://orcid.org/0000-0002-6562-8806"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ojas Pradhan","raw_affiliation_strings":["Drexel University, United States of America"],"affiliations":[{"raw_affiliation_string":"Drexel University, United States of America","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039645001","display_name":"Jin Wen","orcid":"https://orcid.org/0000-0002-1964-8574"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jin Wen","raw_affiliation_strings":["Drexel University, United States of America"],"affiliations":[{"raw_affiliation_string":"Drexel University, United States of America","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064963674","display_name":"Mengyuan Chu","orcid":"https://orcid.org/0009-0000-3354-7537"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengyuan Chu","raw_affiliation_strings":["Texas A&amp;M University, USA"],"affiliations":[{"raw_affiliation_string":"Texas A&amp;M University, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031520161","display_name":"Zheng O\u2019Neill","orcid":"https://orcid.org/0000-0002-8839-7174"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng O'Neill","raw_affiliation_strings":["Texas A&amp;M University, United States of America"],"affiliations":[{"raw_affiliation_string":"Texas A&amp;M University, United States of America","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009233055"],"corresponding_institution_ids":["https://openalex.org/I72816309"],"apc_list":null,"apc_paid":null,"fwci":0.5445,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66891245,"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":"296","last_page":"297"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T14470","display_name":"Advanced Data Processing Techniques","score":0.9818000197410583,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9811999797821045,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.840538501739502},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7374330163002014},{"id":"https://openalex.org/keywords/dynamic-bayesian-network","display_name":"Dynamic Bayesian network","score":0.7182735204696655},{"id":"https://openalex.org/keywords/modelica","display_name":"Modelica","score":0.7124221324920654},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6853364706039429},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.649635910987854},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.6213627457618713},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5334855318069458},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5296615958213806},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3589942753314972},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.322137713432312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32086247205734253},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.1245039701461792}],"concepts":[{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.840538501739502},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7374330163002014},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.7182735204696655},{"id":"https://openalex.org/C37785467","wikidata":"https://www.wikidata.org/wiki/Q385325","display_name":"Modelica","level":2,"score":0.7124221324920654},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6853364706039429},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.649635910987854},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.6213627457618713},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5334855318069458},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5296615958213806},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3589942753314972},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.322137713432312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32086247205734253},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.1245039701461792},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3600100.3626268","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3600100.3626268","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1110189281","display_name":null,"funder_award_id":"EE0009150","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W2110575115","https://openalex.org/W2131694827","https://openalex.org/W2991860176","https://openalex.org/W4361026914"],"related_works":["https://openalex.org/W2357836719","https://openalex.org/W2578973671","https://openalex.org/W2215058820","https://openalex.org/W2945000716","https://openalex.org/W2097663773","https://openalex.org/W1602184117","https://openalex.org/W2564827943","https://openalex.org/W2511198839","https://openalex.org/W1966557338","https://openalex.org/W2366931106"],"abstract_inverted_index":{"A":[0],"dynamic":[1],"Bayesian":[2],"Network":[3],"(DBN)-based":[4],"fault":[5,17,41,71],"prognosis":[6],"framework":[7,24,64],"is":[8,51],"proposed":[9,23,49],"in":[10,28,68],"this":[11],"study":[12],"to":[13,37],"predict":[14],"the":[15,26,39,48,54,62],"future":[16,40,70],"probabilities":[18,72],"of":[19,47,73],"gradual":[20,74],"faults.":[21,75],"The":[22,43],"utilizes":[25],"trend":[27],"prediction":[29],"error":[30],"generated":[31],"from":[32,56],"data":[33,55],"driven":[34],"forecasting":[35],"models":[36],"estimate":[38],"beliefs.":[42],"accuracy":[44],"and":[45],"scalability":[46],"method":[50],"evaluated":[52],"using":[53],"a":[57],"Modelica-based":[58],"virtual":[59],"testbed.":[60],"Overall,":[61],"developed":[63],"demonstrates":[65],"good":[66],"potential":[67],"estimating":[69]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
