Data partitioning and association mining for identifying VRF energy consumption patterns under various part loads and refrigerant charge conditions-Reference-Cited by-同舟云学术

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Data partitioning and association mining for identifying VRF energy consumption patterns under various part loads and refrigerant charge conditions

Published:2017-01 Issue: Volume:185 Page:846-861
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Li Guannan,Hu Yunpeng,Chen Huanxin,Li Haorong,Hu Min,Guo Yabin,Liu Jiangyan,Sun Shaobo,Sun Miao

Funder

National Natural Science Foundation of China

state key laboratory of compressor technology, China

Publisher

Elsevier BV

Subject

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

Reference57 articles.

1. A review on the basics of building energy estimation;Fumo;Renew Sustain Energy Rev,2014

2. Application of adaptive neuro-fuzzy methodology for estimating building energy consumption;Naji;Renew Sustain Energy Rev,2016

3. International Energy Agency (IEA), 2013 .

4. Thermal comfort and building energy consumption implications – a review;Yang;Appl Energy,2014

5. Comparative study of the cooling energy performance of variable refrigerant flow systems and variable air volume systems in office buildings;Yu;Appl Energy,2016

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