Thermal load prediction and operation optimization of office building with a zone-level artificial neural network and rule-based control-Reference-Cited by-同舟云学术

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Thermal load prediction and operation optimization of office building with a zone-level artificial neural network and rule-based control

Published:2021-10 Issue: Volume:300 Page:117429
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Hu Jingfan,Zheng Wandong,Zhang Sirui,Li Hao,Liu Zijian,Zhang Guo,Yang Xu

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference46 articles.

1. IEA. Global Status Report for Buildings and Construction 2019; 2019.

2. Assessment of deep recurrent neural network-based strategies for short-term building energy predictions;Fan;Appl Energy,2019

3. Energy analysis of a building using artificial neural network: A review;Kumar;Energy Build,2013

4. Evaluation of flashover voltage levels of contaminated hydrophobic polymer insulators using regression trees, neural networks, and adaptive neuro-fuzzy;Abo-Elyousr;TELKOMNIKA (Telecommunication Computing Electronics and Control),2018

5. Auditing and design evaluation of building automation and control systems based on eu.bac system audit – Danish case study;Engvang;Energy Built Environ,2021

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