Predicting Structural Temperature of Ancient City Walls: A Case Study Using Ambient Temperature and Deep Learning-Reference-Cited by-同舟云学术

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Predicting Structural Temperature of Ancient City Walls: A Case Study Using Ambient Temperature and Deep Learning

Published:2024-07-17 Issue: Volume: Page:1-18
ISSN:1558-3058
Container-title:International Journal of Architectural Heritage
language:en
Short-container-title:International Journal of Architectural Heritage

Author:

Ju Hanwen¹^ORCID,Zhao Yingjie¹^ORCID,Zheng Liang¹,Deng Yang¹²^ORCID,Li Aiqun¹²

Affiliation:

1. School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing, China

2. International Joint Laboratory of Safety and Energy Conservation for Ancient Buildings, Ministry of Education, Beijing, China

Funder

National Natural Science Foundation of China

Outstanding Youth Fund of Beijing University of Civil Engineering and Architecture

Fundamental Research Funds for Beijing University of Civil Engineering and Architecture

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/15583058.2024.2380414

Reference47 articles.

1. Active use of panoramic mobile mapping systems for as built surveying and heritage documentation

2. Failure modes classification and failure mechanism research of ancient city wall

3. Applicability of energy consumption prediction models in a department store: A case study

4. Thermal error prediction model of high-speed motorized spindle based on DELM network optimized by weighted mean of vectors algorithm

5. Abnormal Data Recovery of Structural Health Monitoring for Ancient City Wall Using Deep Learning Neural Network

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