Journal article 336 views
Virtual mix design: Prediction of compressive strength of concrete with industrial wastes using deep data augmentation
Ning Chen,
Shibo Zhao,
Zhiwei Gao 
,
Dawei Wang,
Pengfei Liu,
Markus Oeser,
Yue Hou,
Linbing Wang
,
Dawei Wang,
Pengfei Liu,
Markus Oeser,
Yue Hou,
Linbing Wang
Construction and Building Materials, Volume: 323, Start page: 126580
Swansea University Author: Yue Hou
Full text not available from this repository: check for access using links below.
DOI (Published version): 10.1016/j.conbuildmat.2022.126580
Abstract
Virtual mix design: Prediction of compressive strength of concrete with industrial wastes using deep data augmentation
| Published in: | Construction and Building Materials |
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| ISSN: | 0950-0618 |
| Published: |
Elsevier BV
2022
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa61797 |
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| Keywords: |
Virtual material design; Compressive strength prediction; Data augmentation; Deep learning; Lightweight model |
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| College: |
Faculty of Science and Engineering |
| Funders: |
This work was supported by the International Research Cooperation Seed Fund of Beijing University of Technology (No. 2021A05), Opening project fund of Materials Service Safety Assessment Facilities (MSAF-2021-109), Talent Promotion Program by Beijing Association for Science and Technology, and the Construction of Service Capability of Scientific and Technological Innovation-Municipal Level of Fundamental Research Funds (Scientific Research Categories) of Beijing City. |
| Start Page: |
126580 |