Evaporation temperature prediction of the refrigerant-direct convective-radiant cooling system based on LSTM neural network-Reference-Cited by-同舟云学术

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Evaporation temperature prediction of the refrigerant-direct convective-radiant cooling system based on LSTM neural network

Published:2025-01 Issue: Volume:258 Page:124693
ISSN:1359-4311
Container-title:Applied Thermal Engineering
language:en
Short-container-title:Applied Thermal Engineering

Author:

Jiang Tingting,Zheng Chenxiao,Wang Hanqing,You Shijun,Zhang Huan,Wang Yaran,Sun Jing,Wu Zhenjing,Zhao Wenyuan,Zheng Jia

Funder

State Key Laboratory of Building Safety and Built Environment

Tianjin Municipal Education Commission

Publisher

Elsevier BV

Reference54 articles.

1. Archetype identification and urban building energy modeling for city-scale buildings based on GIS datasets;Deng;Building Simulation,2022

2. Low-carbon building heating system coupled with semiconductor radiation heating and distributed PV: A simulation analysis in two Chinese climate zones;Zhang;Building Simulation,2023

3. Novel radiation-adjustable heating terminal based on flat heat pipe combined with air source heat pump;Wu;Engineering,2023

4. Numerical analysis of cooling potential and indoor thermal comfort with a novel hybrid radiant cooling system in hot and humid climates;Liu;Indoor and Built Environment,2022

5. A field study of occupant thermal comfort with radiant ceiling cooling and overhead air distribution system;Tian;Energy and Buildings,2020

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1. Risk Prediction and Control Study of a Multitower Separation Process Based on DQRA and Bi-LSTM;ACS Sustainable Chemistry & Engineering;2025-01-13

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