{"id":"https://openalex.org/W4293812087","doi":"https://doi.org/10.1109/tits.2022.3200906","title":"A Dynamic Deep Reinforcement Learning-Bayesian Framework for Anomaly Detection","display_name":"A Dynamic Deep Reinforcement Learning-Bayesian Framework for Anomaly Detection","publication_year":2022,"publication_date":"2022-08-31","ids":{"openalex":"https://openalex.org/W4293812087","doi":"https://doi.org/10.1109/tits.2022.3200906"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3200906","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3200906","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-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/A5079517460","display_name":"Jeremy Watts","orcid":"https://orcid.org/0000-0001-9573-264X"},"institutions":[{"id":"https://openalex.org/I2802706902","display_name":"Knoxville College","ror":"https://ror.org/02bxrp522","country_code":"US","type":"education","lineage":["https://openalex.org/I2802706902"]},{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jeremy Watts","raw_affiliation_strings":["Department of Industrial and Systems Engineering, The University of Tennessee Knoxville, Knoxville, TN, USA"],"raw_orcid":"https://orcid.org/0000-0001-9573-264X","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, The University of Tennessee Knoxville, Knoxville, TN, USA","institution_ids":["https://openalex.org/I2802706902","https://openalex.org/I75027704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032338988","display_name":"Franco van Wyk","orcid":"https://orcid.org/0000-0002-4025-6698"},"institutions":[{"id":"https://openalex.org/I26092322","display_name":"Stellenbosch University","ror":"https://ror.org/05bk57929","country_code":"ZA","type":"education","lineage":["https://openalex.org/I26092322"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Franco Van Wyk","raw_affiliation_strings":["Department of Industrial Engineering, Stellenbosch University, Stellenbosch, South Africa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Stellenbosch University, Stellenbosch, South Africa","institution_ids":["https://openalex.org/I26092322"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083801109","display_name":"Shahrbanoo Rezaei","orcid":"https://orcid.org/0000-0002-1196-1611"},"institutions":[{"id":"https://openalex.org/I2802706902","display_name":"Knoxville College","ror":"https://ror.org/02bxrp522","country_code":"US","type":"education","lineage":["https://openalex.org/I2802706902"]},{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shahrbanoo Rezaei","raw_affiliation_strings":["Department of Industrial and Systems Engineering, The University of Tennessee Knoxville, Knoxville, TN, USA"],"raw_orcid":"https://orcid.org/0000-0002-1196-1611","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, The University of Tennessee Knoxville, Knoxville, TN, USA","institution_ids":["https://openalex.org/I2802706902","https://openalex.org/I75027704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100775829","display_name":"Yiyang Wang","orcid":"https://orcid.org/0000-0002-6478-7282"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiyang Wang","raw_affiliation_strings":["Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-6478-7282","affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083290583","display_name":"Neda Masoud","orcid":"https://orcid.org/0000-0002-6526-3317"},"institutions":[{"id":"https://openalex.org/I2802706902","display_name":"Knoxville College","ror":"https://ror.org/02bxrp522","country_code":"US","type":"education","lineage":["https://openalex.org/I2802706902"]},{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Neda Masoud","raw_affiliation_strings":["Department of Industrial and Systems Engineering, The University of Tennessee Knoxville, Knoxville, TN, USA"],"raw_orcid":"https://orcid.org/0000-0002-6526-3317","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, The University of Tennessee Knoxville, Knoxville, TN, USA","institution_ids":["https://openalex.org/I2802706902","https://openalex.org/I75027704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005681030","display_name":"Anahita Khojandi","orcid":"https://orcid.org/0000-0001-6818-2048"},"institutions":[{"id":"https://openalex.org/I2802706902","display_name":"Knoxville College","ror":"https://ror.org/02bxrp522","country_code":"US","type":"education","lineage":["https://openalex.org/I2802706902"]},{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anahita Khojandi","raw_affiliation_strings":["Department of Industrial and Systems Engineering, The University of Tennessee Knoxville, Knoxville, TN, USA"],"raw_orcid":"https://orcid.org/0000-0001-6818-2048","affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, The University of Tennessee Knoxville, Knoxville, TN, USA","institution_ids":["https://openalex.org/I2802706902","https://openalex.org/I75027704"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5079517460"],"corresponding_institution_ids":["https://openalex.org/I2802706902","https://openalex.org/I75027704"],"apc_list":null,"apc_paid":null,"fwci":5.4105,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.96217512,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"23","issue":"12","first_page":"22884","last_page":"22894"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994000196456909,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9994000196456909,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T12761","display_name":"Data Stream Mining Techniques","score":0.9710000157356262,"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/anomaly-detection","display_name":"Anomaly detection","score":0.7867292165756226},{"id":"https://openalex.org/keywords/partially-observable-markov-decision-process","display_name":"Partially observable Markov decision process","score":0.7283584475517273},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7123269438743591},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.6621661186218262},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5712247490882874},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5589830279350281},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.541437029838562},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.48069268465042114},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46526291966438293},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.46358275413513184},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3984297513961792},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.3162515163421631},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.3129887580871582},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10264348983764648}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7867292165756226},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.7283584475517273},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7123269438743591},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.6621661186218262},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5712247490882874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5589830279350281},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.541437029838562},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.48069268465042114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46526291966438293},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.46358275413513184},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3984297513961792},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.3162515163421631},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.3129887580871582},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10264348983764648},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3200906","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3200906","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1584139447","https://openalex.org/W1922658220","https://openalex.org/W1964274671","https://openalex.org/W1972019130","https://openalex.org/W2010942717","https://openalex.org/W2038505590","https://openalex.org/W2099005886","https://openalex.org/W2099419573","https://openalex.org/W2104593144","https://openalex.org/W2105497548","https://openalex.org/W2116520617","https://openalex.org/W2122646361","https://openalex.org/W2145339207","https://openalex.org/W2212765426","https://openalex.org/W2224471783","https://openalex.org/W2278186031","https://openalex.org/W2509583637","https://openalex.org/W2543335630","https://openalex.org/W2593182419","https://openalex.org/W2735942800","https://openalex.org/W2746553466","https://openalex.org/W2786827964","https://openalex.org/W2806741695","https://openalex.org/W2890707978","https://openalex.org/W2932010921","https://openalex.org/W2945434604","https://openalex.org/W2953384591","https://openalex.org/W2963451564","https://openalex.org/W2963864421","https://openalex.org/W2964043796","https://openalex.org/W3106543020","https://openalex.org/W4214717370","https://openalex.org/W4220793930","https://openalex.org/W4254182148","https://openalex.org/W6631190155","https://openalex.org/W6674615465","https://openalex.org/W6684921986","https://openalex.org/W6692846177","https://openalex.org/W6713134421"],"related_works":["https://openalex.org/W2096013579","https://openalex.org/W1589140671","https://openalex.org/W1760611253","https://openalex.org/W52153049","https://openalex.org/W2951545791","https://openalex.org/W1515117609","https://openalex.org/W2294884454","https://openalex.org/W2806741695","https://openalex.org/W4323315247","https://openalex.org/W3169161914"],"abstract_inverted_index":{"To":[0,25],"assure":[1,124],"the":[2,38,47,54,59,79,86,89,149,180,185,199,207,214],"successful":[3],"operation":[4],"of":[5,40,88,102,151],"connected":[6],"and":[7,15,65,126,157],"automated":[8],"vehicles,":[9],"it":[10,92,105],"is":[11,49,61,63,106],"critical":[12],"to":[13,76,95,97,108,120,123,147,224],"detect":[14,225],"isolate":[16],"anomalous":[17,41,62],"and/or":[18],"faulty":[19],"information":[20,42,48],"in":[21,34,100,118,145,203],"a":[22,44,67,83,132,137,152,170],"timely":[23],"manner.":[24],"do":[26],"so,":[27],"anomaly":[28,142,160,200,226],"detection":[29],"techniques":[30],"should":[31],"be":[32],"implemented":[33],"real-time":[35,204],"where":[36],"if":[37],"probability":[39],"exceeds":[43],"certain":[45],"threshold,":[46],"dealt":[50],"with":[51,169],"accordingly.":[52],"Traditionally,":[53],"threshold":[55,117,139,202],"for":[56,78,140],"judging":[57],"whether":[58],"data":[60],"fixed":[64],"determined":[66],"priori.":[68],"However,":[69],"not":[70],"only":[71],"does":[72],"this":[73,116],"approach":[74,111],"fail":[75],"account":[77],"feedback":[80],"obtained":[81],"during":[82],"trip":[84],"on":[85,164],"performance":[87],"algorithms,":[90],"but":[91],"also":[93],"fails":[94],"respond":[96],"potential":[98],"changes":[99],"rates":[101],"anomalies.":[103],"Hence,":[104],"important":[107],"develop":[109,131,156],"an":[110,141,159],"that":[112,205,213],"can":[113],"dynamically":[114],"alter":[115],"response":[119],"exogenous":[121],"factors":[122],"reliable":[125],"robust":[127],"system":[128],"operation.":[129],"We":[130,178],"mathematical":[133],"framework":[134],"which":[135],"utilizes":[136],"dynamic":[138],"classification":[143,161,201],"algorithm":[144,162],"order":[146],"maximize":[148],"safety":[150],"trip.":[153],"Specifically,":[154],"we":[155],"pair":[158],"based":[163],"convolutional":[165],"neural":[166],"networks":[167],"(CNN),":[168],"partially":[171],"observable":[172],"Markov":[173],"decision":[174],"process":[175],"(POMDP)":[176],"model.":[177],"solve":[179],"resulting":[181],"POMDP":[182,215],"model":[183,216],"using":[184],"asynchronous":[186],"advantage":[187],"actor":[188],"critic":[189],"(A3C)":[190],"deep":[191],"reinforcement":[192],"learning":[193],"algorithm.":[194],"The":[195],"prescribed":[196],"policy":[197],"determines":[198],"maximizes":[206],"performance.":[208],"Our":[209],"numerical":[210],"experiments":[211],"show":[212],"outperforms":[217],"state-of-the-art":[218],"benchmarks,":[219],"especially":[220],"under":[221],"more":[222],"difficult":[223],"profiles.":[227]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
