Machine learning vs. hybrid machine learning model for optimal operation of a chiller-Reference-Cited by-同舟云学术

Machine learning vs. hybrid machine learning model for optimal operation of a chiller

Published:2018-09-26 Issue:2 Volume:25 Page:209-220
ISSN:2374-4731
Container-title:Science and Technology for the Built Environment
language:en
Short-container-title:Science and Technology for the Built Environment

Author:

Park SungHo¹,Ahn Ki Uhn²,Hwang Seungho³,Choi Sunkyu³,Park Cheol Soo⁴

Affiliation:

1. Department of Convergence Engineering for Future City, Sungkyunkwan University, Suwon, Gyeonggi, South Korea;

2. School of Civil and Architectural Engineering, Sungkyunkwan University, Suwon, Gyeonggi, South Korea;

3. Energy DT Development Team, SK Telecom Co. Ltd., Seoul, South Korea;

4. Department of Architecture and Architectural Engineering, Institute of Construction and Environmental Engineering, Seoul National University, Seoul, South Korea

Funder

SK Telecom Co.

Korea Ministry of Land, Infrastructure and Transport

Institute of Construction and Environmental Engineering

Publisher

Informa UK Limited

Subject

Fluid Flow and Transfer Processes,Building and Construction,Environmental Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/23744731.2018.1510270

Reference48 articles.

1. Review of modeling methods for HVAC systems

2. Theory and applications of HVAC control systems – A review of model predictive control (MPC)

3. Gaussian Process Model for Control of an Existing Building

4. Simulation, implementation and monitoring of heat pump load shifting using a predictive controller

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