{"id":"https://openalex.org/W4411103843","doi":"https://doi.org/10.3390/a18060351","title":"An RMSprop-Incorporated Latent Factorization of Tensor Model for Random Missing Data Imputation in Structural Health Monitoring","display_name":"An RMSprop-Incorporated Latent Factorization of Tensor Model for Random Missing Data Imputation in Structural Health Monitoring","publication_year":2025,"publication_date":"2025-06-06","ids":{"openalex":"https://openalex.org/W4411103843","doi":"https://doi.org/10.3390/a18060351"},"language":"en","primary_location":{"id":"doi:10.3390/a18060351","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18060351","pdf_url":null,"source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/a18060351","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063439671","display_name":"Jingjing Yang","orcid":"https://orcid.org/0000-0003-2751-2930"},"institutions":[{"id":"https://openalex.org/I63371133","display_name":"Chongqing Jiaotong University","ror":"https://ror.org/01t001k65","country_code":"CN","type":"education","lineage":["https://openalex.org/I63371133"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jingjing Yang","raw_affiliation_strings":["School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 400074, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 400074, China","institution_ids":["https://openalex.org/I63371133"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5063439671"],"corresponding_institution_ids":["https://openalex.org/I63371133"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05557398,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"6","first_page":"351","last_page":"351"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13018","display_name":"Seismology and Earthquake Studies","score":0.9667999744415283,"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/T13018","display_name":"Seismology and Earthquake Studies","score":0.9667999744415283,"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9365000128746033,"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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.9276000261306763,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/imputation","display_name":"Imputation (statistics)","score":0.7315827012062073},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.6634862422943115},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5024247169494629},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3686065673828125},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34757667779922485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33495283126831055},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3014522194862366},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18456336855888367}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.7315827012062073},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6634862422943115},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5024247169494629},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3686065673828125},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34757667779922485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33495283126831055},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3014522194862366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18456336855888367}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/a18060351","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18060351","pdf_url":null,"source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:bbf7b7688d924a11b47af95ee0d6b26f","is_oa":true,"landing_page_url":"https://doaj.org/article/bbf7b7688d924a11b47af95ee0d6b26f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 18, Iss 6, p 351 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/a18060351","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a18060351","pdf_url":null,"source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G648862429","display_name":null,"funder_award_id":"62205039","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":27,"referenced_works":["https://openalex.org/W2781761393","https://openalex.org/W2907017794","https://openalex.org/W2967327527","https://openalex.org/W2990393280","https://openalex.org/W3019396605","https://openalex.org/W3043579284","https://openalex.org/W3048824092","https://openalex.org/W3118283916","https://openalex.org/W3133747210","https://openalex.org/W3160385264","https://openalex.org/W4206695332","https://openalex.org/W4210777925","https://openalex.org/W4225768156","https://openalex.org/W4296295606","https://openalex.org/W4312325321","https://openalex.org/W4315777877","https://openalex.org/W4321019951","https://openalex.org/W4382600228","https://openalex.org/W4392151718","https://openalex.org/W4392406000","https://openalex.org/W4392963331","https://openalex.org/W4399221896","https://openalex.org/W4401326982","https://openalex.org/W4404293887","https://openalex.org/W4406842980","https://openalex.org/W4406856920","https://openalex.org/W4409488671"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W2055961818","https://openalex.org/W2903115227","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3179858851","https://openalex.org/W2081476516","https://openalex.org/W2581984549"],"abstract_inverted_index":{"In":[0],"structural":[1,17],"health":[2],"monitoring":[3],"(SHM),":[4],"ensuring":[5],"data":[6,21,37,165],"completeness":[7],"is":[8],"critical":[9],"for":[10,50,163],"enhancing":[11],"the":[12,137],"accuracy":[13,128,152],"and":[14,66,76,125,136,153,160],"reliability":[15],"of":[16,43,91,145],"condition":[18],"assessments.":[19],"SHM":[20],"are":[22],"prone":[23],"to":[24,29,73,102,130],"random":[25],"missing":[26,164],"values":[27],"due":[28],"signal":[30],"interference":[31],"or":[32],"connectivity":[33],"issues,":[34],"making":[35],"precise":[36],"imputation":[38,68,127,151],"essential.":[39],"A":[40],"latent":[41,89],"factorization":[42,90],"tensor":[44,92],"(LFT)-based":[45],"method":[46],"has":[47],"proven":[48],"effective":[49],"such":[51],"problems,":[52],"with":[53,143],"optimization":[54],"typically":[55],"achieved":[56],"via":[57],"stochastic":[58],"gradient":[59,109],"descent":[60],"(SGD).":[61],"However,":[62],"SGD-based":[63,134],"LFT":[64,135],"models":[65,132],"other":[67],"methods":[69],"exhibit":[70],"significant":[71],"sensitivity":[72],"learning":[74,99],"rates":[75],"slow":[77],"tail-end":[78],"convergence.":[79],"To":[80],"address":[81],"these":[82],"limitations,":[83],"this":[84],"study":[85],"proposes":[86],"an":[87,97],"RMSprop-incorporated":[88],"(RLFT)":[93],"model,":[94],"which":[95],"integrates":[96],"adaptive":[98],"rate":[100],"mechanism":[101],"dynamically":[103],"adjust":[104],"step":[105],"sizes":[106],"based":[107],"on":[108,113],"magnitudes.":[110],"Experimental":[111],"validation":[112],"a":[114,157],"scaled":[115],"bridge":[116],"accelerometer":[117],"dataset":[118],"demonstrates":[119],"that":[120],"RLFT":[121],"achieves":[122],"faster":[123],"convergence":[124,154],"higher":[126],"compared":[129],"state-of-the-art":[131],"including":[133],"long":[138],"short-term":[139],"memory":[140],"(LSTM)":[141],"network,":[142],"improvements":[144],"at":[146],"least":[147],"10%":[148],"in":[149,167],"both":[150],"rate,":[155],"offering":[156],"more":[158],"efficient":[159],"reliable":[161],"solution":[162],"handling":[166],"SHM.":[168]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}