{"id":"https://openalex.org/W7108229470","doi":"https://doi.org/10.1109/lsp.2025.3639375","title":"Addressing Missing Data in Thermal Power Plant Monitoring With Hybrid Attention Time Series Imputation","display_name":"Addressing Missing Data in Thermal Power Plant Monitoring With Hybrid Attention Time Series Imputation","publication_year":2025,"publication_date":"2025-12-02","ids":{"openalex":"https://openalex.org/W7108229470","doi":"https://doi.org/10.1109/lsp.2025.3639375"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2025.3639375","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3639375","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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":null,"display_name":"Liusong Huang","orcid":"https://orcid.org/0009-0007-5769-4663"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liusong Huang","raw_affiliation_strings":["School of Computer and Information Engineering, Maanshan Teacher&#x0027;s College, Maanshan, China"],"raw_orcid":"https://orcid.org/0009-0007-5769-4663","affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Maanshan Teacher&#x0027;s College, Maanshan, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Adam Amril bin Jaharadak","orcid":"https://orcid.org/0000-0001-8441-1621"},"institutions":[{"id":"https://openalex.org/I1336834208","display_name":"Management and Science University","ror":"https://ror.org/027zr9y17","country_code":"MY","type":"education","lineage":["https://openalex.org/I1336834208"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Adam Amril bin Jaharadak","raw_affiliation_strings":["Faculty of Information Sciences and Engineering, Management and Science University, ShahAlam, Malaysia"],"raw_orcid":"https://orcid.org/0000-0001-8441-1621","affiliations":[{"raw_affiliation_string":"Faculty of Information Sciences and Engineering, Management and Science University, ShahAlam, Malaysia","institution_ids":["https://openalex.org/I1336834208"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Nor Izzati Ahmad","orcid":"https://orcid.org/0000-0003-0682-0002"},"institutions":[{"id":"https://openalex.org/I1336834208","display_name":"Management and Science University","ror":"https://ror.org/027zr9y17","country_code":"MY","type":"education","lineage":["https://openalex.org/I1336834208"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Nor Izzati Ahmad","raw_affiliation_strings":["Faculty of Information Sciences and Engineering, Management and Science University, ShahAlam, Malaysia"],"raw_orcid":"https://orcid.org/0000-0003-0682-0002","affiliations":[{"raw_affiliation_string":"Faculty of Information Sciences and Engineering, Management and Science University, ShahAlam, Malaysia","institution_ids":["https://openalex.org/I1336834208"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jie Wang","orcid":"https://orcid.org/0009-0005-6035-1018"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wang","raw_affiliation_strings":["School of Computer and Information Engineering, Maanshan Teacher&#x0027;s College, Maanshan, China"],"raw_orcid":"https://orcid.org/0009-0005-6035-1018","affiliations":[{"raw_affiliation_string":"School of Computer and Information Engineering, Maanshan Teacher&#x0027;s College, Maanshan, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"last","author":{"id":null,"display_name":"Dalin Zhang","orcid":"https://orcid.org/0000-0002-5869-6544"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dalin Zhang","raw_affiliation_strings":["Space Information Research Institute, Hangzhou Dianzi University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5869-6544","affiliations":[{"raw_affiliation_string":"Space Information Research Institute, Hangzhou Dianzi University, Hangzhou, China","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.51223861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"536","last_page":"540"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.4456000030040741,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.4456000030040741,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.15530000627040863,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.13120000064373016,"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/time-series","display_name":"Time series","score":0.5759999752044678},{"id":"https://openalex.org/keywords/novelty-detection","display_name":"Novelty detection","score":0.5716000199317932},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5715000033378601},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5552999973297119},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5085999965667725},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.49079999327659607},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.4332999885082245},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.42289999127388}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7184000015258789},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6079999804496765},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5759999752044678},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.5716000199317932},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5715000033378601},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5552999973297119},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5085999965667725},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.49079999327659607},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.4332999885082245},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.42289999127388},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.42149999737739563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3921000063419342},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36820000410079956},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.33959999680519104},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.32190001010894775},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.29319998621940613},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C4311470","wikidata":"https://www.wikidata.org/wiki/Q159719","display_name":"Power station","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2662000060081482},{"id":"https://openalex.org/C200749887","wikidata":"https://www.wikidata.org/wiki/Q1165574","display_name":"System monitoring","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C115575686","wikidata":"https://www.wikidata.org/wiki/Q18822403","display_name":"Soft sensor","level":3,"score":0.2558000087738037},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.2549000084400177},{"id":"https://openalex.org/C2039551","wikidata":"https://www.wikidata.org/wiki/Q200297","display_name":"Thermal power station","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2025.3639375","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2025.3639375","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5510681867599487}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2891381594","https://openalex.org/W2897782922","https://openalex.org/W2979624870","https://openalex.org/W3038712311","https://openalex.org/W3174697924","https://openalex.org/W4280554461","https://openalex.org/W4312685826","https://openalex.org/W4312863243","https://openalex.org/W4319335604","https://openalex.org/W4323664057","https://openalex.org/W4388430598","https://openalex.org/W4401863520","https://openalex.org/W4401863578","https://openalex.org/W4405518113","https://openalex.org/W4410343047","https://openalex.org/W4412825811","https://openalex.org/W4412876831","https://openalex.org/W4414360835"],"related_works":[],"abstract_inverted_index":{"Thermal":[0],"power":[1,130],"plants":[2],"rely":[3],"on":[4,143,148],"extensive":[5],"sensor":[6,105],"networks":[7],"to":[8,19,84,113],"monitor":[9],"key":[10,144],"operational":[11,122],"parameters,":[12],"yet":[13],"harsh":[14],"industrial":[15,168],"environments":[16],"often":[17],"lead":[18],"incomplete":[20],"data":[21],"characterized":[22],"by":[23,141],"significant":[24,136],"noise,":[25],"complex":[26,167],"physical":[27,117],"dependencies,":[28,101],"and":[29,37,72],"abrupt":[30,121],"state":[31],"transitions.":[32],"This":[33,107],"impedes":[34],"accurate":[35],"monitoring":[36,165],"predictive":[38],"analyses.":[39],"To":[40],"address":[41],"these":[42],"domain-specific":[43],"challenges,":[44],"we":[45],"propose":[46],"a":[47,124,128,149],"novel":[48],"Hybrid":[49],"Multi-Head":[50],"Attention":[51],"(HybridMHA)":[52],"model":[53,85,112,133],"for":[54,162],"time":[55],"series":[56],"imputation.":[57],"The":[58,170],"core":[59],"novelty":[60],"of":[61,69,89],"our":[62,132],"approach":[63],"lies":[64],"in":[65,166],"the":[66,77,86,93,111,159],"synergistic":[67],"combination":[68],"diagonally-masked":[70,78],"self-attention":[71],"dynamic":[73,94],"sparse":[74,95,116],"attention.":[75],"Specifically,":[76],"component":[79,96],"strictly":[80],"preserves":[81],"temporal":[82],"causality":[83],"sequential":[87],"evolution":[88],"plant":[90],"states,":[91],"while":[92],"selectively":[97],"identifies":[98],"critical":[99],"cross-variable":[100],"effectively":[102],"filtering":[103],"out":[104],"noise.":[106],"tailored":[108],"design":[109],"enables":[110],"robustly":[114],"capture":[115],"inter-dependencies":[118],"even":[119],"during":[120],"shifts.Using":[123],"real-world":[125],"dataset":[126,152],"from":[127],"thermal":[129],"plant,":[131],"demonstrates":[134],"statistically":[135],"improvements,":[137],"outperforming":[138],"existing":[139],"methods":[140],"10%\u201320%":[142],"metrics.":[145],"Further":[146],"validation":[147],"public":[150],"benchmark":[151],"confirms":[153],"its":[154],"generalizability.":[155],"These":[156],"findings":[157],"highlight":[158],"model's":[160],"potential":[161],"robust":[163],"real-time":[164],"applications.":[169],"code":[171],"is":[172],"publicly":[173],"available":[174],"at:":[175],"<uri":[176],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[177],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/huangls2024/ImputationTSD</uri>.":[178]},"counts_by_year":[],"updated_date":"2026-01-26T23:06:41.788003","created_date":"2025-12-03T00:00:00"}