Hybrid model using Bayesian neural network for variable refrigerant flow system-Reference-Cited by-同舟云学术

Hybrid model using Bayesian neural network for variable refrigerant flow system

Published:2021-12-16 Issue:1 Volume:15 Page:1-20
ISSN:1940-1493
Container-title:Journal of Building Performance Simulation
language:en
Short-container-title:Journal of Building Performance Simulation

Author:

Ahn Ki Uhn¹,Park Cheol Soo²,Kim Kyung-Jae³,Kim Deuk-Woo¹,Chae Chang-U⁴

Affiliation:

1. Department of Building Research, Korea Institute of Civil Engineering and Building Technology, Goyang-Si, South Korea

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

3. Development Group, Digital Appliance Business, Samsung Electronics, Suwon, South Korea

4. Research Strategic Planning Department, Korea Institute of Civil Engineering and Building Technology, Goyang-Si, South Korea

Funder

Ministry of Land, Infrastructure and Transport of Korean government

Publisher

Informa UK Limited

Subject

Computer Science Applications,Modeling and Simulation,Building and Construction,Architecture

Link

https://www.tandfonline.com/doi/pdf/10.1080/19401493.2021.1992013

Reference55 articles.

1. Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

2. Black-box modeling of residential HVAC system and comparison of gray-box and black-box modeling methods

3. Gray-box modeling and validation of residential HVAC system for control system design

4. Artificial neural network (ANN) based model predictive control (MPC) and optimization of HVAC systems: A state of the art review and case study of a residential HVAC system

5. Local vs. integrated control of a variable refrigerant flow system using artificial neural networks

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