Enhancing mix proportion design of low carbon concrete for shield segment using a combination of Bayesian optimization-NGBoost and NSGA-III algorithm-Reference-Cited by-同舟云学术

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Enhancing mix proportion design of low carbon concrete for shield segment using a combination of Bayesian optimization-NGBoost and NSGA-III algorithm

Published:2024-08 Issue: Volume:465 Page:142746
ISSN:0959-6526
Container-title:Journal of Cleaner Production
language:en
Short-container-title:Journal of Cleaner Production

Author:

Cao Yuan^ORCID,Su Feiming,Antwi-Afari Maxwell Fordjour,Lei Jian,Wu Xianguo,Liu Yang^ORCID

Publisher

Elsevier BV

Reference82 articles.

1. Constrained multi-objective optimization algorithms: review and comparison with application in reinforced concrete structures;Afshari;Appl. Soft Comput.,2019

2. Strength development of mortars containing ground granulated blast-furnace slag: effect of curing temperature and determination of apparent activation energies;Barnett;Cement Concr. Res.,2006

3. Prediction and multi-objective optimization of high-strength concrete parameters via soft computing approaches;Baykasoğlu;Expert Syst. Appl.,2009

4. Literature review on policies to mitigate GHG emissions for cement and concrete;Busch;Resour. Conserv. Recycl.,2022

5. Application of hybrid intelligent algorithm for multi-objective optimization of high performance concrete in complex alpine environment highway;Cao;Construct. Build. Mater.,2023

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2. Multisource information fusion for real-time prediction and multiobjective optimization of large-diameter slurry shield attitude;Reliability Engineering & System Safety;2024-10

3. Optimization of energy-saving retrofit solutions for existing buildings: A multidimensional data fusion approach;Renewable and Sustainable Energy Reviews;2024-09

4. Predicting existing tunnel deformation from adjacent foundation pit construction using hybrid machine learning;Automation in Construction;2024-09

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