{"id":"https://openalex.org/W7225808384","doi":"https://doi.org/10.3390/app162211160","title":"An Interpretable and Automated Optimized Stacking Learning Model for Predicting the Shear Capacity of Reinforced Concrete Beams","display_name":"An Interpretable and Automated Optimized Stacking Learning Model for Predicting the Shear Capacity of Reinforced Concrete Beams","publication_year":2026,"publication_date":"2026-11-11","ids":{"openalex":"https://openalex.org/W7225808384","doi":"https://doi.org/10.3390/app162211160"},"language":"en","primary_location":{"id":"doi:10.3390/app162211160","doi":"https://doi.org/10.3390/app162211160","is_oa":true,"landing_page_url":"https://doi.org/10.3390/app162211160","pdf_url":null,"source":{"id":"https://openalex.org/S4210205812","display_name":"Applied Sciences","issn_l":"2076-3417","issn":["2076-3417"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","oarl","poland-100","russia-white-list-2","vabb-shw"],"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":"Applied Sciences","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/app162211160","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100423703","display_name":"Zheng Liu","orcid":"https://orcid.org/0000-0002-8522-565X","observed_orcids":["https://orcid.org/0000-0002-8522-565X"]},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Liu","raw_affiliation_strings":["School of Civil Engineering and Future Cities, Ningbo University, Ningbo 315211, China"],"raw_orcid":"https://orcid.org/0009-0008-3861-6253","affiliations":[{"raw_affiliation_string":"School of Civil Engineering and Future Cities, Ningbo University, Ningbo 315211, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161484778","display_name":"Yiheng Ding","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiheng Ding","raw_affiliation_strings":["School of Civil Engineering and Future Cities, Ningbo University, Ningbo 315211, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Civil Engineering and Future Cities, Ningbo University, Ningbo 315211, China","institution_ids":["https://openalex.org/I109935558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101495809","display_name":"Wen Xie","orcid":"https://orcid.org/0000-0002-5231-5173","observed_orcids":["https://orcid.org/0000-0002-5231-5173"]},"institutions":[{"id":"https://openalex.org/I109935558","display_name":"Ningbo University","ror":"https://ror.org/03et85d35","country_code":"CN","type":"education","lineage":["https://openalex.org/I109935558"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wen Xie","raw_affiliation_strings":["School of Civil Engineering and Future Cities, Ningbo University, Ningbo 315211, China"],"raw_orcid":"https://orcid.org/0000-0002-5231-5173","affiliations":[{"raw_affiliation_string":"School of Civil Engineering and Future Cities, Ningbo University, Ningbo 315211, China","institution_ids":["https://openalex.org/I109935558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101495809"],"corresponding_institution_ids":["https://openalex.org/I109935558"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2896},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2896},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"22","first_page":"11160","last_page":"11160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10479","display_name":"Structural Behavior of Reinforced Concrete","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10479","display_name":"Structural Behavior of Reinforced Concrete","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12940","display_name":"Structural Engineering and Materials Analysis","score":0.0019000000320374966,"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/T10713","display_name":"Structural Load-Bearing Analysis","score":0.0013000000035390258,"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":[],"concepts":[{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.6539000272750854},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.546500027179718},{"id":"https://openalex.org/C96035792","wikidata":"https://www.wikidata.org/wiki/Q43606218","display_name":"Shear (geology)","level":2,"score":0.49950000643730164},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4968000054359436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4968000054359436},{"id":"https://openalex.org/C2988805333","wikidata":"https://www.wikidata.org/wiki/Q184190","display_name":"Reinforced concrete","level":2,"score":0.489300012588501},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.42179998755455017},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.4106000065803528},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3939000070095062},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.3483999967575073},{"id":"https://openalex.org/C127893833","wikidata":"https://www.wikidata.org/wiki/Q7492185","display_name":"Shear strength (soil)","level":3,"score":0.33970001339912415},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33820000290870667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3375000059604645},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.33169999718666077},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31619998812675476},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3149999976158142},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.31060001254081726},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2985999882221222},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2793000042438507},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C126661757","wikidata":"https://www.wikidata.org/wiki/Q4925641","display_name":"Random search","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2556999921798706},{"id":"https://openalex.org/C168834538","wikidata":"https://www.wikidata.org/wiki/Q3705329","display_name":"Beam (structure)","level":2,"score":0.2556000053882599}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/app162211160","doi":"https://doi.org/10.3390/app162211160","is_oa":true,"landing_page_url":"https://doi.org/10.3390/app162211160","pdf_url":null,"source":{"id":"https://openalex.org/S4210205812","display_name":"Applied Sciences","issn_l":"2076-3417","issn":["2076-3417"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","oarl","poland-100","russia-white-list-2","vabb-shw"],"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":"Applied Sciences","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/app162211160","doi":"https://doi.org/10.3390/app162211160","is_oa":true,"landing_page_url":"https://doi.org/10.3390/app162211160","pdf_url":null,"source":{"id":"https://openalex.org/S4210205812","display_name":"Applied Sciences","issn_l":"2076-3417","issn":["2076-3417"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","oarl","poland-100","russia-white-list-2","vabb-shw"],"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":"Applied Sciences","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,10,35,89,108,115,122,172,179,196],"limited":[3],"predictive":[4,127],"accuracy":[5,128],"of":[6,38,91,107,161],"existing":[7],"models":[8],"and":[9,44,71,86,95,104,111,129,134,150,166,206,210],"challenges":[11],"in":[12,186],"optimizing":[13],"stacking":[14,21,116],"models,":[15,136],"this":[16],"study":[17],"proposes":[18],"an":[19],"interpretable":[20],"learning":[22],"model":[23,50,110],"that":[24,121],"is":[25],"automatically":[26,85],"optimized":[27],"using":[28,54],"a":[29,158,183,191],"genetic":[30],"algorithm":[31,80],"(GA)":[32],"to":[33,84,99,132,143,171],"predict":[34],"shear":[36,173,187,197,214],"capacity":[37,215],"reinforced":[39],"concrete":[40],"(RC)":[41],"beams":[42],"with":[43],"without":[45],"stirrups.":[46],"A":[47,74],"diverse":[48],"candidate":[49],"pool":[51],"was":[52,81,97],"constructed":[53],"11":[55],"classical":[56],"regression":[57],"algorithms":[58],"spanning":[59],"five":[60],"major":[61],"domains:":[62],"ensemble":[63],"learning,":[64],"neural":[65],"networks,":[66],"Bayesian":[67],"theory,":[68],"kernel":[69],"methods,":[70],"nonlinear":[72],"fitting.":[73],"Tree-structured":[75],"Parzen":[76],"Estimator":[77],"(TPE)-based":[78],"optimization":[79,103],"then":[82],"employed":[83],"finely":[87],"tune":[88],"hyperparameters":[90],"each":[92],"individual":[93],"model,":[94],"GA":[96],"introduced":[98],"perform":[100],"global":[101,149],"automated":[102],"dynamic":[105],"updating":[106],"base":[109],"meta-model":[112],"combinations":[113],"within":[114],"architecture.":[117],"The":[118],"results":[119],"demonstrate":[120],"proposed":[123],"GA-Stacking":[124],"exhibits":[125],"excellent":[126],"generalization":[130],"compared":[131],"R-Stacking":[133],"code-based":[135],"while":[137],"achieving":[138],"search":[139],"efficiency":[140],"far":[141],"superior":[142],"random":[144],"search.":[145],"In":[146],"addition,":[147],"both":[148],"local":[151],"Shapley":[152],"additive":[153],"explanations":[154],"(SHAP)":[155],"analyses":[156],"indicate":[157],"positive":[159],"correlation":[160],"section":[162],"geometry":[163],"(b,":[164],"h0)":[165],"material":[167],"strength":[168],"(fc,":[169],"fsv)":[170],"capacity.":[174],"For":[175],"\u03bb":[176],"<":[177],"2.80,":[178],"SHAP":[180],"predictions":[181],"exhibit":[182],"pronounced":[184],"enhancement":[185],"capacity,":[188],"followed":[189],"by":[190],"subsequent":[192],"degradation":[193],"trend":[194],"as":[195],"span-to-depth":[198],"ratio":[199],"increases.":[200],"These":[201],"findings":[202],"provide":[203],"valuable":[204],"methods":[205],"insights":[207],"for":[208],"studying":[209],"applying":[211],"RC":[212],"beam":[213],"prediction.":[216]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2026-11-12T00:00:00"}