{"id":"https://openalex.org/W4401726201","doi":"https://doi.org/10.1109/jiot.2024.3446570","title":"Deep Koopman Predictors for Anomaly Detection of Complex IoT Systems With Time Series Data","display_name":"Deep Koopman Predictors for Anomaly Detection of Complex IoT Systems With Time Series Data","publication_year":2024,"publication_date":"2024-08-21","ids":{"openalex":"https://openalex.org/W4401726201","doi":"https://doi.org/10.1109/jiot.2024.3446570"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2024.3446570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3446570","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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/A5041781809","display_name":"Liu Fu","orcid":"https://orcid.org/0000-0001-9674-452X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liu Fu","raw_affiliation_strings":["National Key Laboratory of Aerospace Power System and Plasma Technology and the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Aerospace Power System and Plasma Technology and the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100762318","display_name":"Meng Ma","orcid":"https://orcid.org/0000-0003-2637-2788"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Ma","raw_affiliation_strings":["National Key Laboratory of Aerospace Power System and Plasma Technology and the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0003-2637-2788","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Aerospace Power System and Plasma Technology and the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049905007","display_name":"Zhi Zhai","orcid":"https://orcid.org/0000-0003-1746-260X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Zhai","raw_affiliation_strings":["National Key Laboratory of Aerospace Power System and Plasma Technology and the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0003-1746-260X","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Aerospace Power System and Plasma Technology and the School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5041781809"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":4.7077,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.95459716,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"11","issue":"23","first_page":"38360","last_page":"38369"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9988999962806702,"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":0.9988999962806702,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9896000027656555,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7691371440887451},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.692327618598938},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6780295372009277},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6679726243019104},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5277859568595886},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5126911401748657},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.501326322555542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3470085859298706},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2716272175312042}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7691371440887451},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.692327618598938},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6780295372009277},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6679726243019104},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5277859568595886},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5126911401748657},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.501326322555542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3470085859298706},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2716272175312042},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/jiot.2024.3446570","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2024.3446570","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[{"id":"https://openalex.org/G598104265","display_name":null,"funder_award_id":"2021M702634","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G677671644","display_name":null,"funder_award_id":"2024T170720","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7410847121","display_name":null,"funder_award_id":"52205124","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1591018827","https://openalex.org/W2014356541","https://openalex.org/W2318412574","https://openalex.org/W2541748320","https://openalex.org/W2676890506","https://openalex.org/W2788229829","https://openalex.org/W2795805775","https://openalex.org/W2957721271","https://openalex.org/W3004178587","https://openalex.org/W3004207920","https://openalex.org/W3004999940","https://openalex.org/W3008244228","https://openalex.org/W3022643593","https://openalex.org/W3035318737","https://openalex.org/W3044515030","https://openalex.org/W3086419524","https://openalex.org/W3105324058","https://openalex.org/W3132782787","https://openalex.org/W3136021864","https://openalex.org/W3155567600","https://openalex.org/W3177318507","https://openalex.org/W3182954817","https://openalex.org/W3184127157","https://openalex.org/W3185928631","https://openalex.org/W3195789587","https://openalex.org/W3198381997","https://openalex.org/W4210693780","https://openalex.org/W4303438998","https://openalex.org/W4310416691","https://openalex.org/W4378945214","https://openalex.org/W4387561305","https://openalex.org/W4391377837","https://openalex.org/W6773555910","https://openalex.org/W6845625448","https://openalex.org/W6846825190","https://openalex.org/W6853479289","https://openalex.org/W6857279128"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,40,59,137],"plays":[2],"an":[3],"important":[4],"role":[5],"in":[6,32],"ensuring":[7],"the":[8,36,94,104,119,122,149],"safety":[9],"and":[10,57,75,79,111,135],"reliability":[11],"of":[12,15,21,38,63,90,96,124,138],"complex":[13,64],"Internet":[14],"Things":[16],"(IoT)":[17],"systems":[18],"through":[19],"analysis":[20],"time-series":[22,42,54],"data.":[23,43],"Generally,":[24],"real-world":[25],"signals":[26],"exhibit":[27],"intrinsic":[28],"nonstationary":[29,61,70,97,113],"characteristics,":[30],"resulting":[31],"a":[33,47],"significant":[34],"challenge":[35],"context":[37],"anomaly":[39,58,125,136],"for":[41,53,121],"In":[44],"this":[45],"study,":[46],"novel":[48],"Wavelet-Koopman":[49,106],"predictor":[50],"is":[51,107],"proposed":[52,67,105,150],"data":[55,71,99,133],"modeling":[56],"underlying":[60],"dynamics":[62],"systems.":[65],"The":[66,88,144],"wavelet-Koopman":[68],"decomposes":[69],"into":[72],"time":[73,76,114],"variant":[74],"invariant":[77],"components":[78],"processes":[80],"them":[81],"separately":[82],"using":[83],"different":[84],"neural":[85],"Koopman":[86],"operators.":[87],"operation":[89],"Wavelet":[91],"decomposition":[92],"avoids":[93],"impact":[95],"temporal":[98],"on":[100,131],"prediction":[101],"results":[102,146],"so":[103],"able":[108],"to":[109],"model":[110],"predict":[112],"series":[115],"data,":[116],"which":[117],"lays":[118],"foundation":[120],"implementation":[123],"detection.":[126],"Several":[127],"experiments":[128],"are":[129,142],"conducted":[130],"common":[132],"sets":[134],"liquid":[139],"rocket":[140],"engines":[141],"realized.":[143],"experimental":[145],"demonstrate":[147],"that":[148],"method":[151],"outperforms":[152],"several":[153],"recent":[154],"methods.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-26T13:28:51.108037","created_date":"2025-10-10T00:00:00"}