{"id":"https://openalex.org/W4409129657","doi":"https://doi.org/10.1109/access.2025.3557571","title":"FreqWave-TranDuD: A Multivariate Time Series Anomaly Detection Method Based on Wavelet and Fourier Transforms","display_name":"FreqWave-TranDuD: A Multivariate Time Series Anomaly Detection Method Based on Wavelet and Fourier Transforms","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409129657","doi":"https://doi.org/10.1109/access.2025.3557571"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3557571","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3557571","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3557571","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108984862","display_name":"Y. H. Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yashi Huang","raw_affiliation_strings":["Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064641785","display_name":"Peishun Liu","orcid":"https://orcid.org/0000-0002-7746-8061"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peishun Liu","raw_affiliation_strings":["Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088236605","display_name":"Rongjia Han","orcid":null},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongjia Han","raw_affiliation_strings":["Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061204988","display_name":"Yin Tian","orcid":"https://orcid.org/0000-0002-4293-6830"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Yin","raw_affiliation_strings":["Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051071198","display_name":"Q. Ping Dou","orcid":"https://orcid.org/0000-0002-6465-1473"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Quanjie Dou","raw_affiliation_strings":["Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044710460","display_name":"Y. SONG","orcid":"https://orcid.org/0009-0004-0459-1677"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibao Song","raw_affiliation_strings":["Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I59028903"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042599107","display_name":"Mengqi Luo","orcid":"https://orcid.org/0000-0002-2629-5340"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengqi Luo","raw_affiliation_strings":["Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Science and Engineering, Ocean University of China, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I59028903"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5108984862"],"corresponding_institution_ids":["https://openalex.org/I59028903"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":8.5354,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.96944619,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"13","issue":null,"first_page":"68384","last_page":"68397"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9970999956130981,"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":0.9970999956130981,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.98089998960495,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9200999736785889,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/wavelet","display_name":"Wavelet","score":0.5906496047973633},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.5610015392303467},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.520966649055481},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5154967904090881},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.5140222311019897},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4917784035205841},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4755028188228607},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.45310303568840027},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4457472264766693},{"id":"https://openalex.org/keywords/fourier-series","display_name":"Fourier series","score":0.4259260892868042},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4215608835220337},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3755069673061371},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3137340545654297},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11579746007919312},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10129910707473755},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.08445191383361816},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.0664374828338623}],"concepts":[{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5906496047973633},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.5610015392303467},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.520966649055481},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5154967904090881},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.5140222311019897},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4917784035205841},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4755028188228607},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.45310303568840027},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4457472264766693},{"id":"https://openalex.org/C207864730","wikidata":"https://www.wikidata.org/wiki/Q179467","display_name":"Fourier series","level":2,"score":0.4259260892868042},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4215608835220337},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3755069673061371},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3137340545654297},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11579746007919312},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10129910707473755},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.08445191383361816},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0664374828338623},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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":2,"locations":[{"id":"doi:10.1109/access.2025.3557571","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3557571","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:b36433c1c44d48e0ad9e8fdd0c1450a7","is_oa":true,"landing_page_url":"https://doaj.org/article/b36433c1c44d48e0ad9e8fdd0c1450a7","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 68384-68397 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3557571","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3557571","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2143781310","display_name":null,"funder_award_id":"2022YFB3305302","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W2089831283","https://openalex.org/W2093805119","https://openalex.org/W2095409369","https://openalex.org/W2191950414","https://openalex.org/W2296719434","https://openalex.org/W2407991977","https://openalex.org/W2604247107","https://openalex.org/W2743617586","https://openalex.org/W2786827964","https://openalex.org/W2900749811","https://openalex.org/W2906498146","https://openalex.org/W2911200746","https://openalex.org/W2950361482","https://openalex.org/W2962736999","https://openalex.org/W3015959599","https://openalex.org/W3031577140","https://openalex.org/W3081497074","https://openalex.org/W3127386226","https://openalex.org/W3128634608","https://openalex.org/W3140570329","https://openalex.org/W3166456567","https://openalex.org/W3169450514","https://openalex.org/W3176476506","https://openalex.org/W3190748826","https://openalex.org/W4205222700","https://openalex.org/W4256177618","https://openalex.org/W4283318673","https://openalex.org/W4295681312","https://openalex.org/W4300672471","https://openalex.org/W4306317275","https://openalex.org/W4320024086","https://openalex.org/W4321636581","https://openalex.org/W4361852364","https://openalex.org/W4388334594","https://openalex.org/W4389117490","https://openalex.org/W4390005500","https://openalex.org/W4390919300","https://openalex.org/W4392303499","https://openalex.org/W4392904165","https://openalex.org/W4395053762","https://openalex.org/W4401008965","https://openalex.org/W6679539681","https://openalex.org/W6748102297","https://openalex.org/W6768819193","https://openalex.org/W6771795890","https://openalex.org/W6797155008","https://openalex.org/W6802061597","https://openalex.org/W6845625448"],"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":{"Time":[0],"series":[1,40,60],"anomaly":[2,61,137],"detection":[3,16,62,150],"(AD)":[4],"plays":[5],"a":[6,57],"crucial":[7],"role":[8],"in":[9,38,118],"network":[10],"systems.":[11],"It":[12],"enables":[13],"the":[14,34,119,132],"timely":[15],"of":[17],"anomalies":[18],"and":[19,49,85,129,151],"root":[20],"cause":[21],"analysis,":[22],"helping":[23],"to":[24,45,71,88,99,114],"prevent":[25],"unnecessary":[26],"losses.":[27],"Existing":[28],"methods":[29],"have":[30],"not":[31],"fully":[32],"exploited":[33],"frequency":[35,66],"information":[36],"embedded":[37],"time":[39,59,120],"data,":[41],"limiting":[42],"their":[43],"ability":[44],"effectively":[46],"capture":[47,100,115],"global":[48,101],"periodic":[50,102],"patterns.":[51,109],"In":[52],"this":[53],"paper,":[54],"we":[55],"propose":[56],"novel":[58],"method":[63,75],"based":[64],"on":[65,141],"domain":[67],"feature":[68],"extraction,":[69],"referred":[70],"as":[72,148],"FreqWave-TranDuD.":[73],"The":[74,122],"adopts":[76],"an":[77],"encoder-decoder":[78,133],"deep":[79],"learning":[80],"architecture,":[81],"integrating":[82],"Fourier":[83,94],"Transform":[84,87,95,106],"Wavelet":[86,105],"extract":[89],"comprehensive":[90],"time-frequency":[91],"information.":[92],"Fast":[93],"(FFT)":[96],"is":[97,112],"used":[98],"patterns,":[103],"while":[104],"captures":[107],"local":[108],"Additionally,":[110],"LSTM":[111],"employed":[113],"temporal":[116],"dependencies":[117],"series.":[121],"extracted":[123],"features":[124],"are":[125],"then":[126],"preliminarily":[127],"concatenated":[128],"fed":[130],"into":[131],"architecture":[134],"for":[135],"accurate":[136],"detection.":[138],"Extensive":[139],"experiments":[140],"six":[142],"public":[143],"datasets":[144],"from":[145],"domains":[146],"such":[147],"aerospace":[149],"water":[152],"treatment":[153],"demonstrate":[154],"that":[155],"our":[156],"method,":[157],"FreqWave-TranDuD,":[158],"outperforms":[159],"other":[160],"advanced":[161],"baseline":[162],"models.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-04T07:04:00.330322","created_date":"2025-10-10T00:00:00"}
