Optimizing durability assessment: Machine learning models for depth of wear of environmentally-friendly concrete-Reference-Cited by-同舟云学术

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Optimizing durability assessment: Machine learning models for depth of wear of environmentally-friendly concrete

Published:2023-12 Issue: Volume:20 Page:101625
ISSN:2590-1230
Container-title:Results in Engineering
language:en
Short-container-title:Results in Engineering

Author:

Khan Majid^ORCID,Nassar Roz-Ud-Din,Khan Asad Ullah,Houda Moustafa,El Hachem Chady,Rasheed Mazhar,Anwar Waqar

Publisher

Elsevier BV

Subject

General Engineering

Reference143 articles.

1. Phase change materials in concrete: an overview of properties;Adesina;Mater. Today Proc.,2020

2. Concrete slab comparison and embodied energy optimisation for alternate design and construction techniques;Miller;Constr. Build. Mater.,2015

3. CO2 emission patterns in shrinking and growing cities: a case study of Northeast China and the Yangtze River Delta;Xiao;Appl. Energy,2019

4. Greenhouse gas emissions in building construction: a case study of One Peking in Hong Kong;Yan;Build. Environ.,2010

5. Global strategies and potentials to curb CO2 emissions in cement industry;Benhelal;J. Clean. Prod.,2013

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