Forecasting the strength of nanocomposite concrete containing carbon nanotubes by interpretable machine learning approaches with graphical user interface

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Li, Tianlong;Yang, Jianyu;Jiang, Pengxiao;Abuhussain, Mohammed Awad;Zaman, Athar;...

通讯作者：

Yang, JY;Farooq, F

作者机构：

[Li, Tianlong] Qionghai Construct Engn Qual & Safety Supervis Stn, Hainan 571442, Peoples R China.

[Yang, JY; Yang, Jianyu] Changsha Univ Sci & Technol, Sch Civil Engn, Changsha 410000, Hunan, Peoples R China.

[Jiang, Pengxiao] China Construct Fifth Engn Div Corp Ltd, Changsha 410000, Peoples R China.

[Abuhussain, Mohammed Awad] Najran Univ, Coll Engn, Architectural Engn Dept, Najran, Saudi Arabia.

[Abuhussain, Mohammed Awad] Najran Univ, Sci & Engn Res Ctr, Najran, Saudi Arabia.

通讯机构：

[Yang, JY ] C

[Farooq, F ] N

Changsha Univ Sci & Technol, Sch Civil Engn, Changsha 410000, Hunan, Peoples R China.

Natl Univ Sci & Technol, NUST Inst Civil Engn, Sch Civil & Environm Engn, Sect H 12, Islamabad 44000, Pakistan.

语种：

英文

关键词：

Nanocomposite;Machine learning;Contour graphs;Heat map;Statistical analysis;Shapley results

期刊：

Structures

ISSN：

2352-0124

年：

2024

卷：

页码：

105821

DOI：

10.1016/j.istruc.2023.105821

基金类别：

This research was supported by National Natural Science Foundation of China (52209155) and Hunan Natural Science Foundation (2020JJ5592). Acknowledgment The authors are thankful to Deanship of Scientific Research and under the supervision of the Science and Engineering Research Centre at Najran University for funding this work under the Research Centers program grant code (NU/RCP/SERC/12/2).

机构署名：

本校为第一且通讯机构

院系归属：

土木工程学院

摘要：

The sustainable development of the construction industry necessitates the utilization of multipurpose Cement Composites (CC). Therefore, the integration of nanomaterials has the potential to provide CC that exhibits superior performance and possesses several functionalities. Hence, the use of Carbon Nanotubes (CNTs) inside the concrete cementitious sector holds significant potential for implementing effective solutions toward creating a sustainable ecosystem characterized by versatile attributes. Nevertheless, the prediction of the characteristics of these composites is a significant challenge...

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Forecasting the strength of nanocomposite concrete containing carbon nanotubes by interpretable machine learning approaches with graphical user interface

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