Application of artificial neural networks for determining energy-efficient operating set-points of the VRF cooling system-Reference-Cited by-同舟云学术

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Application of artificial neural networks for determining energy-efficient operating set-points of the VRF cooling system

Published:2017-11 Issue: Volume:125 Page:77-87
ISSN:0360-1323
Container-title:Building and Environment
language:en
Short-container-title:Building and Environment

Author:

Chung Min Hee,Yang Young Kwon,Lee Kwang Ho,Lee Je Hyeon,Moon Jin Woo

Funder

Department of Digital Appliance R&D Team, Samsung Electronics

Basic Science Research Program through the National Research Foundation (NRF) of Korea

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Subject

Building and Construction,Geography, Planning and Development,Civil and Structural Engineering,Environmental Engineering

Reference30 articles.

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3. Impacts of climate change on energy consumption and peak demand in buildings: a detailed regional approach;Dirks;Energy,2015

4. Impact of climate change heating and cooling energy use in buildings in the United States;Wang;Energy Build.,2014

5. The variation of climate change impact on building energy consumption to building type and spatiotemporal scale;Huang;Energy,2016

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