Prediction of ultimate bearing capacity for rubberized concrete filled steel tube columns based on Tabular Variational Autoencoder method and Stacking ensemble strategy
The application of rubberized concrete filled steel tube (RuCFST) structures can facilitate the recycling of used tires, offering a sustainable solution. In recent years, data-driven machine learning (ML) algorithms have garnered significant attention from researchers in the engineering field. Howev...
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| Veröffentlicht in: | Structures (Oxford) Jg. 70; S. 107667 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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01.12.2024
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| ISSN: | 2352-0124, 2352-0124 |
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| Abstract | The application of rubberized concrete filled steel tube (RuCFST) structures can facilitate the recycling of used tires, offering a sustainable solution. In recent years, data-driven machine learning (ML) algorithms have garnered significant attention from researchers in the engineering field. However, the development of ML models for predicting the ultimate bearing capacity of RuCFST columns has been hindered by a lack of sufficient experimental data. To address this limitation, this study develops a novel ML framework aimed at accurately predicting the ultimate bearing capacity of RuCFST columns. This framework integrates an advanced Tabular Variational Autoencoder (TVAE) data augmentation method and a Stacking ensemble strategy. The TVAE method generates reliable synthetic data to enhance the dataset, while the Stacking strategy integrates the strengths of various ML models, including Gradient Boosting Decision Tree, Extreme Gradient Boosting, Light Gradient Boosting Machine, Random Forest, and Ridge, to improve prediction accuracy. The predictive validity of the developed TVAE-Stacking model was assessed against other ensemble methods and commonly used machine learning models. The findings indicated that the TVAE-Stacking model excels in predicting the ultimate bearing capacity of RuCFST columns. This model serves as a valuable reference for applying RuCFST columns in structural engineering. |
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| AbstractList | The application of rubberized concrete filled steel tube (RuCFST) structures can facilitate the recycling of used tires, offering a sustainable solution. In recent years, data-driven machine learning (ML) algorithms have garnered significant attention from researchers in the engineering field. However, the development of ML models for predicting the ultimate bearing capacity of RuCFST columns has been hindered by a lack of sufficient experimental data. To address this limitation, this study develops a novel ML framework aimed at accurately predicting the ultimate bearing capacity of RuCFST columns. This framework integrates an advanced Tabular Variational Autoencoder (TVAE) data augmentation method and a Stacking ensemble strategy. The TVAE method generates reliable synthetic data to enhance the dataset, while the Stacking strategy integrates the strengths of various ML models, including Gradient Boosting Decision Tree, Extreme Gradient Boosting, Light Gradient Boosting Machine, Random Forest, and Ridge, to improve prediction accuracy. The predictive validity of the developed TVAE-Stacking model was assessed against other ensemble methods and commonly used machine learning models. The findings indicated that the TVAE-Stacking model excels in predicting the ultimate bearing capacity of RuCFST columns. This model serves as a valuable reference for applying RuCFST columns in structural engineering. |
| ArticleNumber | 107667 |
| Author | Zhang, Chao Lu, Yiyan Song, Zongming |
| Author_xml | – sequence: 1 givenname: Zongming surname: Song fullname: Song, Zongming organization: School of Civil Engineering, Wuhan University, Wuhan 430072, China – sequence: 2 givenname: Chao surname: Zhang fullname: Zhang, Chao email: chao.zhang@whu.edu.cn organization: School of Civil Engineering, Wuhan University, Wuhan 430072, China – sequence: 3 givenname: Yiyan surname: Lu fullname: Lu, Yiyan email: yylu901@163.com organization: School of Civil Engineering, Wuhan University, Wuhan 430072, China |
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| Cites_doi | 10.1016/j.jclepro.2011.11.066 10.1016/j.autcon.2022.104579 10.1016/j.engstruct.2021.111979 10.1016/j.autcon.2022.104297 10.1016/j.jclepro.2015.07.081 10.1038/s42256-019-0138-9 10.1016/j.conbuildmat.2020.122216 10.1016/j.engstruct.2016.12.049 10.1016/j.ress.2021.108223 10.1016/j.autcon.2021.103977 10.1016/j.engstruct.2023.115675 10.1007/s13296-022-00693-0 10.1016/j.engstruct.2016.01.018 10.1016/j.jclepro.2021.126032 10.1016/j.jclepro.2015.03.012 10.1109/JBHI.2020.3027443 10.1016/j.tws.2012.03.008 10.1007/s40091-019-0228-2 10.1016/j.istruc.2022.05.022 10.1016/j.engstruct.2022.115066 10.1080/10618600.1998.10474784 10.1016/j.jclepro.2017.02.046 10.1016/j.jclepro.2022.135279 10.1016/j.jcsr.2011.04.001 10.1016/j.aei.2020.101126 10.1016/j.engstruct.2019.05.048 10.1016/j.jcsr.2012.10.005 10.1016/j.compstruct.2022.115651 10.1016/j.rineng.2021.100316 10.1214/12-STS406 10.1016/j.asoc.2024.111353 10.1061/(ASCE)ST.1943-541X.0003392 10.1016/j.compstruct.2022.115381 10.1016/j.jcsr.2013.07.001 10.1016/j.engstruct.2021.113479 10.1016/j.tws.2019.02.031 10.1007/s40996-022-00893-y 10.1016/j.conbuildmat.2022.129232 10.1016/j.tws.2022.110125 10.1007/s10115-007-0114-2 10.1016/j.conbuildmat.2022.129504 10.1016/j.eswa.2023.122071 10.1109/TII.2024.3366993 10.1016/j.jclepro.2013.10.028 10.1016/j.jclepro.2017.09.131 10.1016/j.jcsr.2010.04.006 10.1016/j.engappai.2022.105151 10.1016/j.jcsr.2009.07.004 10.1016/j.conbuildmat.2022.126694 10.1016/j.jmrt.2022.10.153 10.1016/S0893-6080(05)80023-1 10.1016/j.jcsr.2019.05.003 |
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| Keywords | Ultimate bearing capacity Tabular variational autoencoder Ensemble learning Stacking Rubberized concrete filled steel tube columns |
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| References | Abed, AlHamaydeh, Abdalla (bib19) 2013; 80 Tan, Zhu, Wu, Chai (bib29) 2024; 241 Wang, Mazumder, Salarieh, Salman, Shafieezadeh, Li (bib1) 2022; 148 Khusru, Fawzia, Thambiratnam, Elchalakani (bib16) 2021; 276 Fu (bib58) 1998; 7 Wolpert (bib52) 1992; 5 Ahmed, Mangalathu, Jeon (bib49) 2022; 46 Wang, Tao, Han, Uy, Lam, Kang (bib20) 2017; 135 Guo, Dai, Si, Sun, Lu (bib15) 2017; 148 Vadyala, Betgeri, Matthews, Matthews (bib33) 2022; 13 Li, Song (bib39) 2022; 324 Bravo, de Brito, Pontes, Evangelista (bib13) 2015; 99 Truong, Chou (bib48) 2022; 143 Mujdeci, Guo, Bompa, Elghazouli (bib26) 2022; 181 Liu, Cao, Wang, Chen, Qin (bib42) 2022; 356 Baucum, Khojandi, Vasudevan (bib30) 2021; 25 Alwanas, Al-Musawi, Salih, Tao, Ali, Yaseen (bib6) 2019; 194 Gupta, Chaudhary, Sharma (bib14) 2016; 112 Hossain, Chu (bib55) 2019; 11 Duong, Le, Le (bib35) 2023; 23 A. Abid, A. Abdalla, A. Abid, D. Khan, A. Alfozan, J. Zou, Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild, (2019). http://arxiv.org/abs/1906.02569 (accessed July 16, 2024). Naser, Thai, Thai (bib31) 2021; 34 Zhaoyuan, Qiyun, Wanlin, Xiaopeng (bib57) 2022; 52 Wakjira, Al-Hamrani, Ebead, Alnahhal (bib3) 2022; 287 Shen, Huang, Liu, Zhou (bib62) 2022; 16 Farooq, Ahmed, Akbar, Aslam, Alyousef (bib37) 2021; 292 Czarnecki, Sadowski, Hoła (bib43) 2021; 132 Feng, Wang, Mangalathu, Hu, Wu (bib41) 2021; 235 Tao, Wang, Yu (bib22) 2013; 89 Saleh, AlHamaydeh, Zakaria (bib45) 2023; 280 Gilpin, Bau, Yuan, Bajwa, Specter, Kagal (bib63) 2018 Mohtasham Moein, Saradar, Rahmati, Ghasemzadeh Mousavinejad, Bristow, Aramali, Karakouzian (bib34) 2023; 63 Dong, Elchalakani, Karrech, Fawzia, Mohamed Ali, Yang, Xu (bib54) 2019; 162 Dundu (bib27) 2012; 56 Zhang, Cheng, Li, Du (bib38) 2022; 50 Huang, Xue, Zhang, Guo (bib4) 2022; 251 de Oliveira, De Nardin, de Cresce El Debs, El Debs (bib21) 2009; 65 Ganaie, Hu, Malik, Tanveer, Suganthan (bib53) 2022; 115 Saleh, Tarawneh, Naser (bib7) 2022; 292 Shafighfard, Bagherzadeh, Rizi, Yoo (bib47) 2022; 21 Duarte, Silva, Silvestre, de Brito, Júlio, Castro (bib24) 2016; 112 Feng, Liu, Wang, Jiang, Liang (bib36) 2020; 45 Cavaleri, Barkhordari, Repapis, Armaghani, Ulrikh, Asteris (bib40) 2022; 359 Wakjira, Alam (bib28) 2024; 154 Zhaoyuan, Qiyun, Wanlin, Jiafeng (bib56) 2022; 41 Li, Li, Hu, Sun, Qin, Chu (bib9) 2024; 20 Bravo, de Brito (bib12) 2012; 25 Blum, Nunes, Prangle, Sisson (bib59) 2013; 28 L. Xu, K. Veeramachaneni, Synthesizing Tabular Data using Generative Adversarial Networks, (2018). http://arxiv.org/abs/1811.11264 (accessed June 17, 2024). Dong, Elchalakani, Karrech, Hassanein, Xie, Yang (bib25) 2019; 139 Huang, Burton (bib8) 2019; 25 Sagi, Rokach (bib60) 2018; 8 Wu, Kumar, Ross Quinlan, Ghosh, Yang, Motoda, McLachlan, Ng, Liu, Yu, Zhou, Steinbach, Hand, Steinberg (bib61) 2008; 14 Li, Song (bib44) 2023; 382 Silvestre, de Brito, Pinheiro (bib11) 2014; 66 Yu, Liang, Samali, Nguyen, Zhai, Li, Xie (bib5) 2022; 273 Arokiaprakash, Selvan (bib32) 2022; 46 Saraygord Afshari, Enayatollahi, Xu, Liang (bib2) 2022; 219 Duarte, Silvestre, de Brito, Júlio, Silvestre (bib23) 2018; 170 Ding, Yu, Bai, Gong (bib18) 2011; 67 L. Xu, M. Skoularidou, A. Cuesta-Infante, K. Veeramachaneni, Modeling Tabular data using Conditional GAN, (n.d.). Chou, Nguyen (bib46) 2022; 140 Lundberg, Erion, Chen, DeGrave, Prutkin, Nair, Katz, Himmelfarb, Bansal, Lee (bib10) 2020; 2 Chitawadagi, Narasimhan, Kulkarni (bib17) 2010; 66 Saleh (10.1016/j.istruc.2024.107667_bib7) 2022; 292 Hossain (10.1016/j.istruc.2024.107667_bib55) 2019; 11 Mohtasham Moein (10.1016/j.istruc.2024.107667_bib34) 2023; 63 Blum (10.1016/j.istruc.2024.107667_bib59) 2013; 28 Khusru (10.1016/j.istruc.2024.107667_bib16) 2021; 276 Saraygord Afshari (10.1016/j.istruc.2024.107667_bib2) 2022; 219 Gupta (10.1016/j.istruc.2024.107667_bib14) 2016; 112 Fu (10.1016/j.istruc.2024.107667_bib58) 1998; 7 Vadyala (10.1016/j.istruc.2024.107667_bib33) 2022; 13 Zhang (10.1016/j.istruc.2024.107667_bib38) 2022; 50 Duong (10.1016/j.istruc.2024.107667_bib35) 2023; 23 Wakjira (10.1016/j.istruc.2024.107667_bib28) 2024; 154 Wolpert (10.1016/j.istruc.2024.107667_bib52) 1992; 5 Wang (10.1016/j.istruc.2024.107667_bib20) 2017; 135 Li (10.1016/j.istruc.2024.107667_bib44) 2023; 382 Mujdeci (10.1016/j.istruc.2024.107667_bib26) 2022; 181 Cavaleri (10.1016/j.istruc.2024.107667_bib40) 2022; 359 Dundu (10.1016/j.istruc.2024.107667_bib27) 2012; 56 Tan (10.1016/j.istruc.2024.107667_bib29) 2024; 241 Naser (10.1016/j.istruc.2024.107667_bib31) 2021; 34 Feng (10.1016/j.istruc.2024.107667_bib41) 2021; 235 Huang (10.1016/j.istruc.2024.107667_bib4) 2022; 251 Wakjira (10.1016/j.istruc.2024.107667_bib3) 2022; 287 Czarnecki (10.1016/j.istruc.2024.107667_bib43) 2021; 132 Farooq (10.1016/j.istruc.2024.107667_bib37) 2021; 292 Sagi (10.1016/j.istruc.2024.107667_bib60) 2018; 8 Wang (10.1016/j.istruc.2024.107667_bib1) 2022; 148 10.1016/j.istruc.2024.107667_bib64 Liu (10.1016/j.istruc.2024.107667_bib42) 2022; 356 Alwanas (10.1016/j.istruc.2024.107667_bib6) 2019; 194 Arokiaprakash (10.1016/j.istruc.2024.107667_bib32) 2022; 46 Silvestre (10.1016/j.istruc.2024.107667_bib11) 2014; 66 Shafighfard (10.1016/j.istruc.2024.107667_bib47) 2022; 21 Dong (10.1016/j.istruc.2024.107667_bib54) 2019; 162 Zhaoyuan (10.1016/j.istruc.2024.107667_bib57) 2022; 52 Yu (10.1016/j.istruc.2024.107667_bib5) 2022; 273 Bravo (10.1016/j.istruc.2024.107667_bib13) 2015; 99 Duarte (10.1016/j.istruc.2024.107667_bib24) 2016; 112 Zhaoyuan (10.1016/j.istruc.2024.107667_bib56) 2022; 41 Dong (10.1016/j.istruc.2024.107667_bib25) 2019; 139 Li (10.1016/j.istruc.2024.107667_bib9) 2024; 20 Ahmed (10.1016/j.istruc.2024.107667_bib49) 2022; 46 10.1016/j.istruc.2024.107667_bib50 Bravo (10.1016/j.istruc.2024.107667_bib12) 2012; 25 10.1016/j.istruc.2024.107667_bib51 Ding (10.1016/j.istruc.2024.107667_bib18) 2011; 67 Feng (10.1016/j.istruc.2024.107667_bib36) 2020; 45 Gilpin (10.1016/j.istruc.2024.107667_bib63) 2018 Guo (10.1016/j.istruc.2024.107667_bib15) 2017; 148 Li (10.1016/j.istruc.2024.107667_bib39) 2022; 324 de Oliveira (10.1016/j.istruc.2024.107667_bib21) 2009; 65 Baucum (10.1016/j.istruc.2024.107667_bib30) 2021; 25 Duarte (10.1016/j.istruc.2024.107667_bib23) 2018; 170 Lundberg (10.1016/j.istruc.2024.107667_bib10) 2020; 2 Ganaie (10.1016/j.istruc.2024.107667_bib53) 2022; 115 Abed (10.1016/j.istruc.2024.107667_bib19) 2013; 80 Saleh (10.1016/j.istruc.2024.107667_bib45) 2023; 280 Tao (10.1016/j.istruc.2024.107667_bib22) 2013; 89 Truong (10.1016/j.istruc.2024.107667_bib48) 2022; 143 Shen (10.1016/j.istruc.2024.107667_bib62) 2022; 16 Chitawadagi (10.1016/j.istruc.2024.107667_bib17) 2010; 66 Chou (10.1016/j.istruc.2024.107667_bib46) 2022; 140 Huang (10.1016/j.istruc.2024.107667_bib8) 2019; 25 Wu (10.1016/j.istruc.2024.107667_bib61) 2008; 14 |
| References_xml | – volume: 292 year: 2021 ident: bib37 article-title: Predictive modeling for sustainable high-performance concrete from industrial wastes: a comparison and optimization of models using ensemble learners publication-title: J Clean Prod – volume: 287 year: 2022 ident: bib3 article-title: Shear capacity prediction of FRP-RC beams using single and ensenble explainable machine learning models publication-title: Compos Struct – volume: 13 year: 2022 ident: bib33 article-title: A review of physics-based machine learning in civil engineering publication-title: Results Eng – volume: 181 year: 2022 ident: bib26 article-title: Axial and bending behaviour of steel tubes infilled with rubberised concrete publication-title: Thin-Walled Struct – volume: 139 start-page: 24 year: 2019 end-page: 38 ident: bib25 article-title: Behaviour and design of rubberised concrete filled steel tubes under combined loading conditions publication-title: Thin-Walled Struct – volume: 63 year: 2023 ident: bib34 article-title: Predictive models for concrete properties using machine learning and deep learning approaches: a review publication-title: J Build Eng – volume: 80 start-page: 429 year: 2013 end-page: 439 ident: bib19 article-title: Experimental and numerical investigations of the compressive behavior of concrete filled steel tubes (CFSTs) publication-title: J Constr Steel Res – volume: 170 start-page: 510 year: 2018 end-page: 521 ident: bib23 article-title: On the sustainability of rubberized concrete filled square steel tubular columns publication-title: J Clean Prod – volume: 21 start-page: 3777 year: 2022 end-page: 3794 ident: bib47 article-title: Data-driven compressive strength prediction of steel fiber reinforced concrete (SFRC) subjected to elevated temperatures using stacked machine learning algorithms publication-title: J Mater Res Technol – volume: 34 year: 2021 ident: bib31 article-title: Evaluating structural response of concrete-filled steel tubular columns through machine learning publication-title: J Build Eng – volume: 25 start-page: 2273 year: 2021 end-page: 2280 ident: bib30 article-title: Improving deep reinforcement learning with transitional variational autoencoders: a healthcare application publication-title: IEEE J Biomed Health Inform – volume: 148 year: 2022 ident: bib1 article-title: Machine learning for risk and resilience assessment in structural engineering: progress and future trends publication-title: J Struct Eng – volume: 45 year: 2020 ident: bib36 article-title: Failure mode classification and bearing capacity prediction for reinforced concrete columns based on ensemble machine learning algorithm publication-title: Adv Eng Inform – volume: 382 year: 2023 ident: bib44 article-title: Prediction of compressive strength of rice husk ash concrete based on stacking ensemble learning model publication-title: J Clean Prod – reference: L. Xu, M. Skoularidou, A. Cuesta-Infante, K. Veeramachaneni, Modeling Tabular data using Conditional GAN, (n.d.). – volume: 14 start-page: 1 year: 2008 end-page: 37 ident: bib61 article-title: Top 10 algorithms in data mining publication-title: Knowl Inf Syst – volume: 89 start-page: 121 year: 2013 end-page: 131 ident: bib22 article-title: Finite element modelling of concrete-filled steel stub columns under axial compression publication-title: J Constr Steel Res – volume: 112 start-page: 274 year: 2016 end-page: 286 ident: bib24 article-title: Tests and design of short steel tubes filled with rubberised concrete publication-title: Eng Struct – volume: 356 year: 2022 ident: bib42 article-title: Prediction of the durability of high-performance concrete using an integrated RF-LSSVM model publication-title: Constr Build Mater – volume: 65 start-page: 2103 year: 2009 end-page: 2110 ident: bib21 article-title: Influence of concrete strength and length/diameter on the axial capacity of CFT columns publication-title: J Constr Steel Res – volume: 235 year: 2021 ident: bib41 article-title: Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements publication-title: Eng Struct – volume: 140 year: 2022 ident: bib46 article-title: Scour depth prediction at bridge piers using metaheuristics-optimized stacking system publication-title: Autom Constr – volume: 41 start-page: 887 year: 2022 end-page: 907 ident: bib56 article-title: Study on axial compressive behavior of circular steel tube confined rubberized concrete stub columns publication-title: Structures – volume: 280 year: 2023 ident: bib45 article-title: Shear capacity prediction for reinforced concrete deep beams with web openings using artificial intelligence methods publication-title: Eng Struct – volume: 251 year: 2022 ident: bib4 article-title: Torsion design of CFRP-CFST columns using a data-driven optimization approach publication-title: Eng Struct – volume: 52 year: 2022 ident: bib57 article-title: Axial compressive behavior of square steel tube confined rubberized concrete stub columns publication-title: J Build Eng – volume: 135 start-page: 209 year: 2017 end-page: 221 ident: bib20 article-title: Strength, stiffness and ductility of concrete-filled steel columns under axial compression publication-title: Eng Struct – volume: 99 start-page: 59 year: 2015 end-page: 74 ident: bib13 article-title: Mechanical performance of concrete made with aggregates from construction and demolition waste recycling plants publication-title: J Clean Prod – volume: 20 start-page: 8628 year: 2024 end-page: 8638 ident: bib9 article-title: Transparent operator network: a fully interpretable network incorporating learnable wavelet operator for intelligent fault diagnosis publication-title: IEEE Trans Ind Inform – volume: 162 year: 2019 ident: bib54 article-title: Circular steel tubes filled with rubberised concrete under combined loading publication-title: J Constr Steel Res – volume: 46 start-page: 4111 year: 2022 end-page: 4130 ident: bib32 article-title: Application of random forest and multi-layer perceptron ANNS in estimating the axial compression capacity of concrete-filled steel tubes publication-title: Iran J Sci Technol Trans Civ Eng – volume: 23 start-page: 263 year: 2023 end-page: 278 ident: bib35 article-title: Practical machine learning application for predicting axial capacity of composite concrete-filled steel tube columns considering effect of cross-sectional shapes publication-title: Int J Steel Struct – volume: 16 year: 2022 ident: bib62 article-title: Axial compressive behavior of rubberized concrete-filled steel tube short columns publication-title: Case Stud Constr Mater – volume: 8 year: 2018 ident: bib60 article-title: Ensemble learning: a survey publication-title: WIREs Data Min Knowl Discov – reference: A. Abid, A. Abdalla, A. Abid, D. Khan, A. Alfozan, J. Zou, Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild, (2019). http://arxiv.org/abs/1906.02569 (accessed July 16, 2024). – start-page: 80 year: 2018 end-page: 89 ident: bib63 article-title: Explaining explanations: an overview of interpretability of machine learning publication-title: 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA) – volume: 359 year: 2022 ident: bib40 article-title: Convolution-based ensemble learning algorithms to estimate the bond strength of the corroded reinforced concrete publication-title: Constr Build Mater – volume: 276 year: 2021 ident: bib16 article-title: Confined rubberised concrete tubular column for high-performance structures – review publication-title: Constr Build Mater – volume: 56 start-page: 62 year: 2012 end-page: 70 ident: bib27 article-title: Compressive strength of circular concrete filled steel tube columns publication-title: Thin-Walled Struct – volume: 148 start-page: 681 year: 2017 end-page: 689 ident: bib15 article-title: Evaluation of properties and performance of rubber-modified concrete for recycling of waste scrap tire publication-title: J Clean Prod – volume: 50 year: 2022 ident: bib38 article-title: Prediction of failure modes, strength, and deformation capacity of RC shear walls through machine learning publication-title: J Build Eng – volume: 5 start-page: 241 year: 1992 end-page: 259 ident: bib52 article-title: Stacked generalization publication-title: Neural Netw – volume: 194 start-page: 220 year: 2019 end-page: 229 ident: bib6 article-title: Load-carrying capacity and mode failure simulation of beam-column joint connection: application of self-tuning machine learning model publication-title: Eng Struct – volume: 132 year: 2021 ident: bib43 article-title: Evaluation of interlayer bonding in layered composites based on non-destructive measurements and machine learning: comparative analysis of selected learning algorithms publication-title: Autom Constr – volume: 25 start-page: 42 year: 2012 end-page: 50 ident: bib12 article-title: Concrete made with used tyre aggregate: durability-related performance publication-title: J Clean Prod – volume: 2 start-page: 56 year: 2020 end-page: 67 ident: bib10 article-title: From local explanations to global understanding with explainable AI for trees publication-title: Nat Mach Intell – volume: 112 start-page: 702 year: 2016 end-page: 711 ident: bib14 article-title: Mechanical and durability properties of waste rubber fiber concrete with and without silica fume publication-title: J Clean Prod – volume: 46 year: 2022 ident: bib49 article-title: Seismic damage state predictions of reinforced concrete structures using stacked long short-term memory neural networks publication-title: J Build Eng – volume: 143 year: 2022 ident: bib48 article-title: Fuzzy adaptive jellyfish search-optimized stacking machine learning for engineering planning and design publication-title: Autom Constr – volume: 66 start-page: 37 year: 2014 end-page: 45 ident: bib11 article-title: Environmental impacts and benefits of the end-of-life of building materials – calculation rules, results and contribution to a “cradle to cradle” life cycle publication-title: J Clean Prod – volume: 11 start-page: 255 year: 2019 end-page: 270 ident: bib55 article-title: Confinement of six different concretes in CFST columns having different shapes and slenderness publication-title: Int J Adv Struct Eng – volume: 7 start-page: 397 year: 1998 end-page: 416 ident: bib58 article-title: Penalized regressions: the bridge versus the Lasso publication-title: J Comput Graph Stat – volume: 25 year: 2019 ident: bib8 article-title: Classification of in-plane failure modes for reinforced concrete frames with infills using machine learning publication-title: J Build Eng – volume: 241 year: 2024 ident: bib29 article-title: DPTVAE: Data-driven prior-based tabular variational autoencoder for credit data synthesizing publication-title: Expert Syst Appl – volume: 292 year: 2022 ident: bib7 article-title: Failure mode classification and deformability evaluation for concrete beams reinforced with FRP bars publication-title: Compos Struct – volume: 273 year: 2022 ident: bib5 article-title: Torsional capacity evaluation of RC beams using an improved bird swarm algorithm optimised 2D convolutional neural network publication-title: Eng Struct – volume: 154 year: 2024 ident: bib28 article-title: Peak and ultimate stress-strain model of confined ultra-high-performance concrete (UHPC) using hybrid machine learning model with conditional tabular generative adversarial network publication-title: Appl Soft Comput – volume: 324 year: 2022 ident: bib39 article-title: High-performance concrete strength prediction based on ensemble learning publication-title: Constr Build Mater – volume: 219 year: 2022 ident: bib2 article-title: Machine learning-based methods in structural reliability analysis: a review publication-title: Reliab Eng Syst Saf – volume: 115 year: 2022 ident: bib53 article-title: Ensemble deep learning: a review publication-title: Eng Appl Artif Intell – volume: 66 start-page: 1248 year: 2010 end-page: 1260 ident: bib17 article-title: Axial strength of circular concrete-filled steel tube columns — DOE approach publication-title: J Constr Steel Res – volume: 28 start-page: 189 year: 2013 end-page: 208 ident: bib59 article-title: A comparative review of dimension reduction methods in approximate bayesian computation publication-title: Stat Sci – volume: 67 start-page: 1567 year: 2011 end-page: 1577 ident: bib18 article-title: Elasto-plastic analysis of circular concrete-filled steel tube stub columns publication-title: J Constr Steel Res – reference: L. Xu, K. Veeramachaneni, Synthesizing Tabular Data using Generative Adversarial Networks, (2018). http://arxiv.org/abs/1811.11264 (accessed June 17, 2024). – volume: 25 start-page: 42 year: 2012 ident: 10.1016/j.istruc.2024.107667_bib12 article-title: Concrete made with used tyre aggregate: durability-related performance publication-title: J Clean Prod doi: 10.1016/j.jclepro.2011.11.066 – volume: 143 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib48 article-title: Fuzzy adaptive jellyfish search-optimized stacking machine learning for engineering planning and design publication-title: Autom Constr doi: 10.1016/j.autcon.2022.104579 – volume: 46 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib49 article-title: Seismic damage state predictions of reinforced concrete structures using stacked long short-term memory neural networks publication-title: J Build Eng – ident: 10.1016/j.istruc.2024.107667_bib50 – volume: 235 year: 2021 ident: 10.1016/j.istruc.2024.107667_bib41 article-title: Implementing ensemble learning methods to predict the shear strength of RC deep beams with/without web reinforcements publication-title: Eng Struct doi: 10.1016/j.engstruct.2021.111979 – volume: 140 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib46 article-title: Scour depth prediction at bridge piers using metaheuristics-optimized stacking system publication-title: Autom Constr doi: 10.1016/j.autcon.2022.104297 – volume: 112 start-page: 702 year: 2016 ident: 10.1016/j.istruc.2024.107667_bib14 article-title: Mechanical and durability properties of waste rubber fiber concrete with and without silica fume publication-title: J Clean Prod doi: 10.1016/j.jclepro.2015.07.081 – volume: 2 start-page: 56 year: 2020 ident: 10.1016/j.istruc.2024.107667_bib10 article-title: From local explanations to global understanding with explainable AI for trees publication-title: Nat Mach Intell doi: 10.1038/s42256-019-0138-9 – volume: 276 year: 2021 ident: 10.1016/j.istruc.2024.107667_bib16 article-title: Confined rubberised concrete tubular column for high-performance structures – review publication-title: Constr Build Mater doi: 10.1016/j.conbuildmat.2020.122216 – volume: 135 start-page: 209 year: 2017 ident: 10.1016/j.istruc.2024.107667_bib20 article-title: Strength, stiffness and ductility of concrete-filled steel columns under axial compression publication-title: Eng Struct doi: 10.1016/j.engstruct.2016.12.049 – volume: 219 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib2 article-title: Machine learning-based methods in structural reliability analysis: a review publication-title: Reliab Eng Syst Saf doi: 10.1016/j.ress.2021.108223 – volume: 132 year: 2021 ident: 10.1016/j.istruc.2024.107667_bib43 article-title: Evaluation of interlayer bonding in layered composites based on non-destructive measurements and machine learning: comparative analysis of selected learning algorithms publication-title: Autom Constr doi: 10.1016/j.autcon.2021.103977 – volume: 280 year: 2023 ident: 10.1016/j.istruc.2024.107667_bib45 article-title: Shear capacity prediction for reinforced concrete deep beams with web openings using artificial intelligence methods publication-title: Eng Struct doi: 10.1016/j.engstruct.2023.115675 – volume: 23 start-page: 263 year: 2023 ident: 10.1016/j.istruc.2024.107667_bib35 article-title: Practical machine learning application for predicting axial capacity of composite concrete-filled steel tube columns considering effect of cross-sectional shapes publication-title: Int J Steel Struct doi: 10.1007/s13296-022-00693-0 – volume: 112 start-page: 274 year: 2016 ident: 10.1016/j.istruc.2024.107667_bib24 article-title: Tests and design of short steel tubes filled with rubberised concrete publication-title: Eng Struct doi: 10.1016/j.engstruct.2016.01.018 – volume: 292 year: 2021 ident: 10.1016/j.istruc.2024.107667_bib37 article-title: Predictive modeling for sustainable high-performance concrete from industrial wastes: a comparison and optimization of models using ensemble learners publication-title: J Clean Prod doi: 10.1016/j.jclepro.2021.126032 – volume: 34 year: 2021 ident: 10.1016/j.istruc.2024.107667_bib31 article-title: Evaluating structural response of concrete-filled steel tubular columns through machine learning publication-title: J Build Eng – volume: 99 start-page: 59 year: 2015 ident: 10.1016/j.istruc.2024.107667_bib13 article-title: Mechanical performance of concrete made with aggregates from construction and demolition waste recycling plants publication-title: J Clean Prod doi: 10.1016/j.jclepro.2015.03.012 – volume: 25 start-page: 2273 year: 2021 ident: 10.1016/j.istruc.2024.107667_bib30 article-title: Improving deep reinforcement learning with transitional variational autoencoders: a healthcare application publication-title: IEEE J Biomed Health Inform doi: 10.1109/JBHI.2020.3027443 – volume: 56 start-page: 62 year: 2012 ident: 10.1016/j.istruc.2024.107667_bib27 article-title: Compressive strength of circular concrete filled steel tube columns publication-title: Thin-Walled Struct doi: 10.1016/j.tws.2012.03.008 – volume: 11 start-page: 255 year: 2019 ident: 10.1016/j.istruc.2024.107667_bib55 article-title: Confinement of six different concretes in CFST columns having different shapes and slenderness publication-title: Int J Adv Struct Eng doi: 10.1007/s40091-019-0228-2 – volume: 41 start-page: 887 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib56 article-title: Study on axial compressive behavior of circular steel tube confined rubberized concrete stub columns publication-title: Structures doi: 10.1016/j.istruc.2022.05.022 – volume: 273 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib5 article-title: Torsional capacity evaluation of RC beams using an improved bird swarm algorithm optimised 2D convolutional neural network publication-title: Eng Struct doi: 10.1016/j.engstruct.2022.115066 – volume: 7 start-page: 397 year: 1998 ident: 10.1016/j.istruc.2024.107667_bib58 article-title: Penalized regressions: the bridge versus the Lasso publication-title: J Comput Graph Stat doi: 10.1080/10618600.1998.10474784 – volume: 148 start-page: 681 year: 2017 ident: 10.1016/j.istruc.2024.107667_bib15 article-title: Evaluation of properties and performance of rubber-modified concrete for recycling of waste scrap tire publication-title: J Clean Prod doi: 10.1016/j.jclepro.2017.02.046 – volume: 382 year: 2023 ident: 10.1016/j.istruc.2024.107667_bib44 article-title: Prediction of compressive strength of rice husk ash concrete based on stacking ensemble learning model publication-title: J Clean Prod doi: 10.1016/j.jclepro.2022.135279 – volume: 67 start-page: 1567 year: 2011 ident: 10.1016/j.istruc.2024.107667_bib18 article-title: Elasto-plastic analysis of circular concrete-filled steel tube stub columns publication-title: J Constr Steel Res doi: 10.1016/j.jcsr.2011.04.001 – volume: 45 year: 2020 ident: 10.1016/j.istruc.2024.107667_bib36 article-title: Failure mode classification and bearing capacity prediction for reinforced concrete columns based on ensemble machine learning algorithm publication-title: Adv Eng Inform doi: 10.1016/j.aei.2020.101126 – volume: 194 start-page: 220 year: 2019 ident: 10.1016/j.istruc.2024.107667_bib6 article-title: Load-carrying capacity and mode failure simulation of beam-column joint connection: application of self-tuning machine learning model publication-title: Eng Struct doi: 10.1016/j.engstruct.2019.05.048 – volume: 80 start-page: 429 year: 2013 ident: 10.1016/j.istruc.2024.107667_bib19 article-title: Experimental and numerical investigations of the compressive behavior of concrete filled steel tubes (CFSTs) publication-title: J Constr Steel Res doi: 10.1016/j.jcsr.2012.10.005 – volume: 292 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib7 article-title: Failure mode classification and deformability evaluation for concrete beams reinforced with FRP bars publication-title: Compos Struct doi: 10.1016/j.compstruct.2022.115651 – volume: 13 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib33 article-title: A review of physics-based machine learning in civil engineering publication-title: Results Eng doi: 10.1016/j.rineng.2021.100316 – volume: 28 start-page: 189 year: 2013 ident: 10.1016/j.istruc.2024.107667_bib59 article-title: A comparative review of dimension reduction methods in approximate bayesian computation publication-title: Stat Sci doi: 10.1214/12-STS406 – volume: 154 year: 2024 ident: 10.1016/j.istruc.2024.107667_bib28 article-title: Peak and ultimate stress-strain model of confined ultra-high-performance concrete (UHPC) using hybrid machine learning model with conditional tabular generative adversarial network publication-title: Appl Soft Comput doi: 10.1016/j.asoc.2024.111353 – volume: 50 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib38 article-title: Prediction of failure modes, strength, and deformation capacity of RC shear walls through machine learning publication-title: J Build Eng – volume: 148 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib1 article-title: Machine learning for risk and resilience assessment in structural engineering: progress and future trends publication-title: J Struct Eng doi: 10.1061/(ASCE)ST.1943-541X.0003392 – volume: 52 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib57 article-title: Axial compressive behavior of square steel tube confined rubberized concrete stub columns publication-title: J Build Eng – volume: 287 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib3 article-title: Shear capacity prediction of FRP-RC beams using single and ensenble explainable machine learning models publication-title: Compos Struct doi: 10.1016/j.compstruct.2022.115381 – volume: 25 year: 2019 ident: 10.1016/j.istruc.2024.107667_bib8 article-title: Classification of in-plane failure modes for reinforced concrete frames with infills using machine learning publication-title: J Build Eng – volume: 89 start-page: 121 year: 2013 ident: 10.1016/j.istruc.2024.107667_bib22 article-title: Finite element modelling of concrete-filled steel stub columns under axial compression publication-title: J Constr Steel Res doi: 10.1016/j.jcsr.2013.07.001 – start-page: 80 year: 2018 ident: 10.1016/j.istruc.2024.107667_bib63 article-title: Explaining explanations: an overview of interpretability of machine learning – volume: 251 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib4 article-title: Torsion design of CFRP-CFST columns using a data-driven optimization approach publication-title: Eng Struct doi: 10.1016/j.engstruct.2021.113479 – volume: 139 start-page: 24 year: 2019 ident: 10.1016/j.istruc.2024.107667_bib25 article-title: Behaviour and design of rubberised concrete filled steel tubes under combined loading conditions publication-title: Thin-Walled Struct doi: 10.1016/j.tws.2019.02.031 – volume: 46 start-page: 4111 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib32 article-title: Application of random forest and multi-layer perceptron ANNS in estimating the axial compression capacity of concrete-filled steel tubes publication-title: Iran J Sci Technol Trans Civ Eng doi: 10.1007/s40996-022-00893-y – volume: 356 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib42 article-title: Prediction of the durability of high-performance concrete using an integrated RF-LSSVM model publication-title: Constr Build Mater doi: 10.1016/j.conbuildmat.2022.129232 – volume: 181 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib26 article-title: Axial and bending behaviour of steel tubes infilled with rubberised concrete publication-title: Thin-Walled Struct doi: 10.1016/j.tws.2022.110125 – volume: 8 year: 2018 ident: 10.1016/j.istruc.2024.107667_bib60 article-title: Ensemble learning: a survey publication-title: WIREs Data Min Knowl Discov – volume: 14 start-page: 1 year: 2008 ident: 10.1016/j.istruc.2024.107667_bib61 article-title: Top 10 algorithms in data mining publication-title: Knowl Inf Syst doi: 10.1007/s10115-007-0114-2 – ident: 10.1016/j.istruc.2024.107667_bib51 – volume: 359 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib40 article-title: Convolution-based ensemble learning algorithms to estimate the bond strength of the corroded reinforced concrete publication-title: Constr Build Mater doi: 10.1016/j.conbuildmat.2022.129504 – volume: 241 year: 2024 ident: 10.1016/j.istruc.2024.107667_bib29 article-title: DPTVAE: Data-driven prior-based tabular variational autoencoder for credit data synthesizing publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2023.122071 – volume: 20 start-page: 8628 year: 2024 ident: 10.1016/j.istruc.2024.107667_bib9 article-title: Transparent operator network: a fully interpretable network incorporating learnable wavelet operator for intelligent fault diagnosis publication-title: IEEE Trans Ind Inform doi: 10.1109/TII.2024.3366993 – volume: 66 start-page: 37 year: 2014 ident: 10.1016/j.istruc.2024.107667_bib11 article-title: Environmental impacts and benefits of the end-of-life of building materials – calculation rules, results and contribution to a “cradle to cradle” life cycle publication-title: J Clean Prod doi: 10.1016/j.jclepro.2013.10.028 – volume: 170 start-page: 510 year: 2018 ident: 10.1016/j.istruc.2024.107667_bib23 article-title: On the sustainability of rubberized concrete filled square steel tubular columns publication-title: J Clean Prod doi: 10.1016/j.jclepro.2017.09.131 – ident: 10.1016/j.istruc.2024.107667_bib64 – volume: 66 start-page: 1248 year: 2010 ident: 10.1016/j.istruc.2024.107667_bib17 article-title: Axial strength of circular concrete-filled steel tube columns — DOE approach publication-title: J Constr Steel Res doi: 10.1016/j.jcsr.2010.04.006 – volume: 115 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib53 article-title: Ensemble deep learning: a review publication-title: Eng Appl Artif Intell doi: 10.1016/j.engappai.2022.105151 – volume: 65 start-page: 2103 year: 2009 ident: 10.1016/j.istruc.2024.107667_bib21 article-title: Influence of concrete strength and length/diameter on the axial capacity of CFT columns publication-title: J Constr Steel Res doi: 10.1016/j.jcsr.2009.07.004 – volume: 324 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib39 article-title: High-performance concrete strength prediction based on ensemble learning publication-title: Constr Build Mater doi: 10.1016/j.conbuildmat.2022.126694 – volume: 16 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib62 article-title: Axial compressive behavior of rubberized concrete-filled steel tube short columns publication-title: Case Stud Constr Mater – volume: 21 start-page: 3777 year: 2022 ident: 10.1016/j.istruc.2024.107667_bib47 article-title: Data-driven compressive strength prediction of steel fiber reinforced concrete (SFRC) subjected to elevated temperatures using stacked machine learning algorithms publication-title: J Mater Res Technol doi: 10.1016/j.jmrt.2022.10.153 – volume: 5 start-page: 241 year: 1992 ident: 10.1016/j.istruc.2024.107667_bib52 article-title: Stacked generalization publication-title: Neural Netw doi: 10.1016/S0893-6080(05)80023-1 – volume: 162 year: 2019 ident: 10.1016/j.istruc.2024.107667_bib54 article-title: Circular steel tubes filled with rubberised concrete under combined loading publication-title: J Constr Steel Res doi: 10.1016/j.jcsr.2019.05.003 – volume: 63 year: 2023 ident: 10.1016/j.istruc.2024.107667_bib34 article-title: Predictive models for concrete properties using machine learning and deep learning approaches: a review publication-title: J Build Eng |
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