Predictive models of embodied carbon emissions in building design phases: Machine learning approaches based on residential buildings in China-Reference-Cited by-同舟云学术

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Predictive models of embodied carbon emissions in building design phases: Machine learning approaches based on residential buildings in China

Published:2024-06 Issue: Volume:258 Page:111595
ISSN:0360-1323
Container-title:Building and Environment
language:en
Short-container-title:Building and Environment

Author:

Zhang Xiaocun^ORCID,Chen Hailiang,Sun Jiayue,Zhang Xueqi

Funder

Natural Science Foundation of Ningbo Municipality

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

Publisher

Elsevier BV

Reference61 articles.

1. National models of climate governance among major emitters;Guy;Nat. Clim. Change,2023

2. 2022 global status report for buildings and construction: towards a zero-emission, efficient and resilient buildings and construction sector,2022

3. 2022 Research Report on Carbon Emissions of China Urban and Rural Construction,2023

4. Decarbonization strategies of building materials used in the construction industry;Sbahieh;Mater. Today: Proc.,2023

5. Assessment and regression of carbon emissions from the building and construction sector in China: a provincial study using machine learning;Zhang;J. Clean. Prod.,2024

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Research on Carbon Emissions and Influencing Factors of Residents’ Lives in Hebei Province;Sustainability;2024-08-07

2. Energy efficient and sustainable design of a multi-story building based on embodied energy and cost;Scientific Reports;2024-07-13

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