A knowledge embedded graph neural network-based cooling load prediction method using dynamic data association-Reference-Cited by-同舟云学术

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A knowledge embedded graph neural network-based cooling load prediction method using dynamic data association

Published:2023-01 Issue: Volume:278 Page:112635
ISSN:0378-7788
Container-title:Energy and Buildings
language:en
Short-container-title:Energy and Buildings

Author:

Chen Zhiwen,Zhao Zhengrun,Deng Qiao,Tang Peng,Yang Chunhua,Li Xinhong,Gui Weihua

Funder

Natural Science Foundation of Hunan Province

Science and Technology Program of Hunan Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Building and Construction,Civil and Structural Engineering

Reference25 articles.

1. N. Somu, G.R. MR, K. Ramamritham, A deep learning framework for building energy consumption forecast, Renew. Sustain. Energy Rev. 137 (2021) 110591.

2. Building operation and energy performance: Monitoring, analysis and optimisation toolkit;Costa;Appl. Energy,2013

3. A short-term building cooling load prediction method using deep learning algorithms;Fan;Appl. Energy,2017

4. Utilizing transfer function method for hourly cooling load calculations;Al-Rabghi;Energy Convers. Manage.,1997

5. A correlation method for predicting monthly and annual cooling loads in direct gain passive solar heated buildings;Schoenau;Energy Convers. Manage.,1989

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