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Graph convolutional networks-based method for uncertainty quantification of building design loads

Jie Lu Zeyu Zheng Chaobo Zhang Yang Zhao Chenxin Feng Ruchi Choudhary

建筑模拟（英文版）2025，Vol.18Issue(2)：321-337,17.

建筑模拟（英文版）2025，Vol.18Issue(2)：321-337,17.DOI:10.1007/s12273-024-1212-8

Graph convolutional networks-based method for uncertainty quantification of building design loads

Jie Lu ¹Zeyu Zheng ²Chaobo Zhang ³Yang Zhao ⁴Chenxin Feng ⁵Ruchi Choudhary⁶

作者信息

1. Institute of Refriqeration and Cryoqenics,Zheiianq University,Hangzhou,China||Energy Efficient Cities Initiative,Department of Engineering,University of Cambridqe,Cambridge,UK
2. Department of Energy Engineering,Zhejiang University,Hangzhou,China
3. Department of the Built Environment,Eindhoven University of Technology,Eindhoven,the Netherlands
4. Institute of Refriqeration and Cryoqenics,Zheiianq University,Hangzhou,China||Key Laboratory of Clean Energy and Carbon Neutrality of Zhejiang Province,Jiaxing Research Institute,Zhejiang University,Jiaxing,China
5. Institute of Refriqeration and Cryoqenics,Zheiianq University,Hangzhou,China
6. Energy Efficient Cities Initiative,Department of Engineering,University of Cambridqe,Cambridge,UK||Data-centric Engineering,The Alan Turing Institute,London,UK
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摘要

关键词

building design loads/uncertainty quantification/data-driven model/graph convolutional networks/Monte Carlo simulation

Key words

building design loads/uncertainty quantification/data-driven model/graph convolutional networks/Monte Carlo simulation

引用本文复制引用

Jie Lu,Zeyu Zheng,Chaobo Zhang,Yang Zhao,Chenxin Feng,Ruchi Choudhary..Graph convolutional networks-based method for uncertainty quantification of building design loads[J].建筑模拟（英文版）,2025,18(2):321-337,17.

基金项目

This work is supported by the National Natural Science Foundation of China(No.52161135202),Hangzhou Key Scientific Research Plan Project(No.2023SZD0028),the Basic Research Funds for the Central Government'Innovative Team of Zhejiang University'(No.2022FZZX01-09),and China Scholarship Fund. （No.52161135202）

建筑模拟（英文版）

ISSN：1996-3599

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