{"id":"https://openalex.org/W4390534762","doi":"https://doi.org/10.1109/tnnls.2023.3347227","title":"A Lightweight Group Transformer-Based Time Series Reduction Network for Edge Intelligence and Its Application in Industrial RUL Prediction","display_name":"A Lightweight Group Transformer-Based Time Series Reduction Network for Edge Intelligence and Its Application in Industrial RUL Prediction","publication_year":2024,"publication_date":"2024-01-03","ids":{"openalex":"https://openalex.org/W4390534762","doi":"https://doi.org/10.1109/tnnls.2023.3347227","pmid":"https://pubmed.ncbi.nlm.nih.gov/38170656"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3347227","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3347227","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5028426177","display_name":"Lei Ren","orcid":"https://orcid.org/0000-0001-6346-6930"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lei Ren","raw_affiliation_strings":["School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","Zhongguancun Laboratory, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Zhongguancun Laboratory, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062426863","display_name":"Haiteng Wang","orcid":"https://orcid.org/0000-0002-7316-3607"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiteng Wang","raw_affiliation_strings":["School of Automation Science and Electrical Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069766035","display_name":"Tingyu Mo","orcid":"https://orcid.org/0000-0002-1468-5659"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingyu Mo","raw_affiliation_strings":["School of Automation Science and Electrical Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Automation Science and Electrical Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049154222","display_name":"Laurence T. Yang","orcid":"https://orcid.org/0000-0002-7986-4244"},"institutions":[{"id":"https://openalex.org/I197191942","display_name":"St. Francis Xavier University","ror":"https://ror.org/01wcaxs37","country_code":"CA","type":"education","lineage":["https://openalex.org/I197191942"]},{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Laurence T. Yang","raw_affiliation_strings":["Department of Computer Science, St. Francis Xavier University, Antigonish, NS, Canada","School of Computer Science and Technology, Hainan University, Haikou, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, St. Francis Xavier University, Antigonish, NS, Canada","institution_ids":["https://openalex.org/I197191942"]},{"raw_affiliation_string":"School of Computer Science and Technology, Hainan University, Haikou, China","institution_ids":["https://openalex.org/I20942203"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5028426177"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":9.3619,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.9851423,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"36","issue":"2","first_page":"3720","last_page":"3729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9987000226974487,"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9987000226974487,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9966999888420105,"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/T14011","display_name":"Elevator Systems and Control","score":0.9901999831199646,"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/transformer","display_name":"Transformer","score":0.6975694894790649},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6887916922569275},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5951198935508728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48364269733428955},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.42236992716789246},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4219932556152344},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.41429567337036133},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3712412714958191},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3269237279891968},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32308220863342285},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2654823064804077},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1255130171775818}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6975694894790649},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6887916922569275},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5951198935508728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48364269733428955},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.42236992716789246},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4219932556152344},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.41429567337036133},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3712412714958191},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3269237279891968},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32308220863342285},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2654823064804077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1255130171775818},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3347227","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3347227","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:38170656","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38170656","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5299999713897705}],"awards":[{"id":"https://openalex.org/G3160825066","display_name":null,"funder_award_id":"62173023","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6608322027","display_name":null,"funder_award_id":"92167108","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7800621295","display_name":null,"funder_award_id":"62225302","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":32,"referenced_works":["https://openalex.org/W2772084711","https://openalex.org/W2910660149","https://openalex.org/W2978540646","https://openalex.org/W2983270123","https://openalex.org/W3006585575","https://openalex.org/W3035030897","https://openalex.org/W3035038672","https://openalex.org/W3035429418","https://openalex.org/W3110068079","https://openalex.org/W3119743098","https://openalex.org/W3126600466","https://openalex.org/W3173407600","https://openalex.org/W3175938759","https://openalex.org/W3181279185","https://openalex.org/W3187544793","https://openalex.org/W4206652641","https://openalex.org/W4210562913","https://openalex.org/W4214661601","https://openalex.org/W4226069359","https://openalex.org/W4310935363","https://openalex.org/W4310982869","https://openalex.org/W4312456926","https://openalex.org/W4312503109","https://openalex.org/W4313059808","https://openalex.org/W4313291175","https://openalex.org/W4319999748","https://openalex.org/W4321020984","https://openalex.org/W4323914173","https://openalex.org/W4360770771","https://openalex.org/W4385245566","https://openalex.org/W4385371079","https://openalex.org/W6779436764"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4231775656","https://openalex.org/W2611989081","https://openalex.org/W2046435967","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W2383646825","https://openalex.org/W4304166257","https://openalex.org/W2371018915"],"abstract_inverted_index":{"Recently,":[0],"deep":[1,45],"learning-based":[2],"models":[3,47],"such":[4],"as":[5],"transformer":[6,64,101],"have":[7],"achieved":[8],"significant":[9],"performance":[10,144],"for":[11,36],"industrial":[12,26],"remaining":[13],"useful":[14],"life":[15],"(RUL)":[16],"prediction":[17,29],"due":[18],"to":[19,51,72,93,104,123,140,165],"their":[20],"strong":[21],"representation":[22],"ability.":[23],"In":[24,58],"many":[25],"practices,":[27],"RUL":[28,80],"algorithms":[30],"are":[31],"deployed":[32],"on":[33,151],"edge":[34,56],"devices":[35],"real-time":[37],"response.":[38],"However,":[39],"the":[40,53,95,143,152,158],"high":[41],"computational":[42],"cost":[43,171],"of":[44,55,145],"learning":[46,136],"makes":[48],"it":[49],"difficult":[50],"meet":[52],"requirements":[54],"intelligence.":[57],"this":[59,74],"article,":[60],"a":[61,98,117,134],"lightweight":[62,99],"group":[63,100,109],"with":[65,112],"multihierarchy":[66,135],"time-series":[67,118,146],"reduction":[68,119],"(GT-MRNet)":[69],"is":[70,102,121,138],"proposed":[71,122,159],"alleviate":[73],"problem.":[75],"Different":[76],"from":[77],"most":[78],"existing":[79],"methods":[81],"computing":[82],"all":[83],"time":[84,91,128],"series,":[85],"GT-MRNet":[86],"can":[87,161],"adaptively":[88,124],"select":[89],"necessary":[90],"steps":[92,129],"compute":[94],"RUL.":[96],"First,":[97],"constructed":[103],"extract":[105],"features":[106],"by":[107],"employing":[108],"linear":[110],"transformation":[111],"significantly":[113,162],"fewer":[114],"parameters.":[115],"Then,":[116],"strategy":[120],"filter":[125],"out":[126],"unimportant":[127],"at":[130],"each":[131],"layer.":[132],"Finally,":[133],"mechanism":[137],"developed":[139],"further":[141],"stabilize":[142],"reduction.":[147],"Extensive":[148],"experimental":[149],"results":[150],"real-world":[153],"condition":[154],"datasets":[155],"demonstrate":[156],"that":[157],"method":[160],"reduce":[163],"up":[164],"74.7%":[166],"parameters":[167],"and":[168],"91.8%":[169],"computation":[170],"without":[172],"sacrificing":[173],"accuracy.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":4}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}