{"id":"https://openalex.org/W7131363632","doi":"https://doi.org/10.1016/j.engappai.2026.114315","title":"Deep learning-based prediction of the hysteretic behavior of buckling-restrained braces for seismic design using analysis-of-mean-based optimal hyperparameters","display_name":"Deep learning-based prediction of the hysteretic behavior of buckling-restrained braces for seismic design using analysis-of-mean-based optimal hyperparameters","publication_year":2026,"publication_date":"2026-02-25","ids":{"openalex":"https://openalex.org/W7131363632","doi":"https://doi.org/10.1016/j.engappai.2026.114315"},"language":"en","primary_location":{"id":"doi:10.1016/j.engappai.2026.114315","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114315","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.engappai.2026.114315","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5126755227","display_name":"Kihoon Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I48566637","display_name":"Ulsan National Institute of Science and Technology","ror":"https://ror.org/017cjz748","country_code":"KR","type":"education","lineage":["https://openalex.org/I48566637"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kihoon Lim","raw_affiliation_strings":["Department of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea","institution_ids":["https://openalex.org/I48566637"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090557420","display_name":"E. Jeong","orcid":null},"institutions":[{"id":"https://openalex.org/I111277659","display_name":"Chonnam National University","ror":"https://ror.org/05kzjxq56","country_code":"KR","type":"education","lineage":["https://openalex.org/I111277659"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Euncheol Jeong","raw_affiliation_strings":["Department of Architectural Design, Chonnam National University, Yeosu City, 59626, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Architectural Design, Chonnam National University, Yeosu City, 59626, Republic of Korea","institution_ids":["https://openalex.org/I111277659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070501566","display_name":"Dave Montellano Osabel","orcid":"https://orcid.org/0000-0001-9097-1721"},"institutions":[{"id":"https://openalex.org/I111277659","display_name":"Chonnam National University","ror":"https://ror.org/05kzjxq56","country_code":"KR","type":"education","lineage":["https://openalex.org/I111277659"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dave Montellano Osabel","raw_affiliation_strings":["Department of Architectural Design, Chonnam National University, Yeosu City, 59626, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0001-9097-1721","affiliations":[{"raw_affiliation_string":"Department of Architectural Design, Chonnam National University, Yeosu City, 59626, Republic of Korea","institution_ids":["https://openalex.org/I111277659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126752579","display_name":"Young K. Ju","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161052","display_name":"Korea University","ror":"https://ror.org/05m1gnk07","country_code":"JP","type":"education","lineage":["https://openalex.org/I4210161052"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Young K. Ju","raw_affiliation_strings":["Department of Civil, Environmental and Architectural Engineering, Korea University, Seoul City, 02841, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil, Environmental and Architectural Engineering, Korea University, Seoul City, 02841, Republic of Korea","institution_ids":["https://openalex.org/I4210161052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126770817","display_name":"Jaehyeok Doh","orcid":null},"institutions":[{"id":"https://openalex.org/I189442560","display_name":"Gyeongsang National University","ror":"https://ror.org/00saywf64","country_code":"KR","type":"education","lineage":["https://openalex.org/I189442560"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jaehyeok Doh","raw_affiliation_strings":["School of Aerospace Engineering, Gyeongsang National University, Jinju City, 52828, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0003-4511-6907","affiliations":[{"raw_affiliation_string":"School of Aerospace Engineering, Gyeongsang National University, Jinju City, 52828, Republic of Korea","institution_ids":["https://openalex.org/I189442560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123102107","display_name":"Jaehoon Bae","orcid":null},"institutions":[{"id":"https://openalex.org/I111277659","display_name":"Chonnam National University","ror":"https://ror.org/05kzjxq56","country_code":"KR","type":"education","lineage":["https://openalex.org/I111277659"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jaehoon Bae","raw_affiliation_strings":["Department of Architectural Design, Chonnam National University, Yeosu City, 59626, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0001-8940-5255","affiliations":[{"raw_affiliation_string":"Department of Architectural Design, Chonnam National University, Yeosu City, 59626, Republic of Korea","institution_ids":["https://openalex.org/I111277659"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5123102107","https://openalex.org/A5126770817"],"corresponding_institution_ids":["https://openalex.org/I111277659","https://openalex.org/I189442560"],"apc_list":{"value":3170,"currency":"USD","value_usd":3170},"apc_paid":{"value":3170,"currency":"USD","value_usd":3170},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39745859,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"171","issue":null,"first_page":"114315","last_page":"114315"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10160","display_name":"Seismic Performance and Analysis","score":0.5971999764442444,"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"}},"topics":[{"id":"https://openalex.org/T10160","display_name":"Seismic Performance and Analysis","score":0.5971999764442444,"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"}},{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.10570000112056732,"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"}},{"id":"https://openalex.org/T10221","display_name":"Composite Structure Analysis and Optimization","score":0.03440000116825104,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/hyperparameter","display_name":"Hyperparameter","score":0.9767000079154968},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6384999752044678},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5981000065803528},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5644000172615051},{"id":"https://openalex.org/keywords/hysteresis","display_name":"Hysteresis","score":0.5407000184059143},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.49149999022483826},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4584999978542328}],"concepts":[{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.9767000079154968},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.745199978351593},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6384999752044678},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5981000065803528},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5644000172615051},{"id":"https://openalex.org/C123299182","wikidata":"https://www.wikidata.org/wiki/Q190837","display_name":"Hysteresis","level":2,"score":0.5407000184059143},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.49149999022483826},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45890000462532043},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4584999978542328},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4262999892234802},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.38530001044273376},{"id":"https://openalex.org/C135628077","wikidata":"https://www.wikidata.org/wiki/Q220184","display_name":"Finite element method","level":2,"score":0.37959998846054077},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.35899999737739563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3314000070095062},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.3255000114440918},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2705000042915344},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.engappai.2026.114315","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114315","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.engappai.2026.114315","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.engappai.2026.114315","pdf_url":null,"source":{"id":"https://openalex.org/S900972176","display_name":"Engineering Applications of Artificial Intelligence","issn_l":"0952-1976","issn":["0952-1976","1873-6769"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Applications of Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.677199125289917,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320327527","display_name":"Ministry of the Interior and Safety","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2107878631","https://openalex.org/W2147765665","https://openalex.org/W2157331557","https://openalex.org/W2598457882","https://openalex.org/W2788697198","https://openalex.org/W2888769947","https://openalex.org/W2908487093","https://openalex.org/W2946752227","https://openalex.org/W2999772350","https://openalex.org/W3041451785","https://openalex.org/W3117275895","https://openalex.org/W3197849304","https://openalex.org/W3198148990","https://openalex.org/W4206382297","https://openalex.org/W4283077069","https://openalex.org/W4284688082","https://openalex.org/W4288949546","https://openalex.org/W4379142701","https://openalex.org/W4390804110","https://openalex.org/W4399880372","https://openalex.org/W4401758384","https://openalex.org/W4404874472","https://openalex.org/W4405319942"],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"aims":[2],"to":[3,25],"develop":[4],"a":[5],"recurrent":[6],"neural":[7],"network":[8],"(RNN)-based":[9],"framework":[10],"for":[11,116,131],"predicting":[12],"the":[13,55,126,142,146,161,177],"nonlinear":[14,184],"hysteretic":[15],"behavior":[16],"of":[17,62,77,81,106,151,165],"phase-change-material-filled":[18],"buckling-restrained":[19],"braces":[20],"(PCM-filled":[21],"BRBs)":[22],"in":[23,149,183],"order":[24],"reduce":[26],"reliance":[27],"on":[28,170],"repeated":[29],"large-scale":[30],"experiments":[31,63],"and":[32,44,79,93,99,108,119,135,153,155],"associated":[33],"testing":[34],"costs.":[35],"Representative":[36],"RNN":[37,56],"architectures,":[38],"including":[39],"Long":[40],"Short-Term":[41],"Memory":[42],"(LSTM)":[43],"Gated":[45],"Recurrent":[46],"Unit":[47],"(GRU)":[48],"networks,":[49],"are":[50,114],"investigated.":[51],"To":[52],"systematically":[53],"configure":[54],"models,":[57],"an":[58],"orthogonal":[59],"array\u2013based":[60],"design":[61],"is":[64,86,102],"employed,":[65],"incorporating":[66],"key":[67],"hyperparameters":[68],"such":[69],"as":[70],"input":[71],"window":[72],"size,":[73,75],"batch":[74],"number":[76,80],"layers,":[78],"neurons.":[82],"Model":[83],"prediction":[84],"accuracy":[85],"evaluated":[87],"using":[88],"mean":[89,95],"absolute":[90],"error":[91,97],"(MAE)":[92],"root":[94],"squared":[96],"(RMSE),":[98],"hyperparameter":[100,112],"sensitivity":[101],"assessed":[103],"through":[104],"analysis":[105],"means":[107],"range":[109],"analysis.":[110,187],"Optimal":[111],"combinations":[113],"identified":[115],"both":[117,132,157],"LSTM":[118,147],"GRU":[120,143],"models.":[121],"Using":[122],"these":[123],"optimal":[124],"settings,":[125],"models":[127,158,175],"predict":[128],"hysteresis":[129,164],"responses":[130],"horizontally":[133],"installed":[134],"inclined":[136],"BRBs.":[137],"The":[138],"results":[139],"indicate":[140],"that":[141,156],"model":[144,148],"outperforms":[145],"terms":[150],"MAE":[152],"RMSE,":[154],"can":[159],"reproduce":[160],"complex":[162],"force\u2013displacement":[163],"PCM-filled":[166],"BRBs":[167],"without":[168],"relying":[169],"explicitly":[171],"defined":[172],"phenomenological":[173],"constitutive":[174],"or":[176],"iterative":[178],"parameter":[179],"calibration":[180],"typically":[181],"required":[182],"finite":[185],"element":[186]},"counts_by_year":[],"updated_date":"2026-02-26T06:29:33.603293","created_date":"2026-02-25T00:00:00"}