Predictive monitoring of built thermal environment using limited sensor data: A deep learning-based spatiotemporal method

Author:

Li YueORCID,Tong ZhemingORCID,Westerdahl Dane,Tong Shuiguang

Funder

Natural Science Foundation of Jiangsu Province

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference41 articles.

1. Biodiversity and the built environment: Implications for the Sustainable Development Goals (SDGs);Opoku;Resour Conserv Recycl,2019

2. Machine-learning-based personal thermal comfort modeling for heat recovery using environmental parameters;Fattahi;Sustainable Energy Technol Assess,2023

3. Multi-objective optimization for energy consumption, visual and thermal comfort performance of educational building (case study: Qeshm Island, Iran);Khani;Sustainable Energy Technol Assess,2022

4. A comparative review on the application of radiant low-temperature heating and high-temperature cooling for energy, thermal comfort, indoor air quality, design and control;Hesaraki;Sustainable Energy Technol Assess,2022

5. Design and thermal performance of an innovative greenhouse;Al Miaari;Sustainable Energy Technol Assess,2023

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