Convolutional neural network-based wind pressure prediction on low-rise buildings-Reference-Cited by-同舟云学术

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Convolutional neural network-based wind pressure prediction on low-rise buildings

Published:2024-06 Issue: Volume:309 Page:118078
ISSN:0141-0296
Container-title:Engineering Structures
language:en
Short-container-title:Engineering Structures

Author:

Huang Youqin,Wu Huifan,Fu Jiyang,Zhang Honghao,Li Haisheng

Funder

National Natural Science Foundation of China

Guangzhou Municipal Science and Technology Bureau

Guangzhou Municipal Science and Technology Project

Higher Education Discipline Innovation Project

Ministry of Science and Technology of the People's Republic of China Department of Science and Technology for Social Development

Publisher

Elsevier BV

Reference30 articles.

1. Low-rise gable roof buildings pressure prediction using deep neural networks;Tian;J Wind Eng Ind Aerodyn,2020

2. Prediction of pressure coefficients on roofs of low buildings using artificial neural networks;Chen;J Wind Eng Ind Aerodyn,2003

3. Effects of roof geometry on tornado-induced structural actions of a low-rise building;Razavi;Eng Struct,2021

4. Prediction of wind-induced pressures on a large gymnasium roof using artificial neural networks;Fu;Comput Struct,2007

5. A new parametric equation for the wind pressure coefficient for low-rise buildings;Muehleisen;Energy Build,2013

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. Developing an integrated prediction model for daylighting, thermal comfort, and energy consumption in residential buildings based on the stacking ensemble learning algorithm;Building Simulation;2024-09-10

2. The prediction on non-Gaussian characteristics of wind pressure for the long-span roof in the mountainous area using proper orthogonal decomposition–deep learning framework;Physics of Fluids;2024-08-01

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