Data-driven methods for building control — A review and promising future directions-Reference-Cited by-同舟云学术

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Data-driven methods for building control — A review and promising future directions

Published:2020-02 Issue: Volume:95 Page:104211
ISSN:0967-0661
Container-title:Control Engineering Practice
language:en
Short-container-title:Control Engineering Practice

Author:

Maddalena Emilio T.,Lian Yingzhao,Jones Colin N.

Funder

Swiss National Science Foundation

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Reference187 articles.

1. Review of modeling methods for HVAC systems;Afram;Applied Thermal Engineering,2014

2. Theory and applications of HVAC control systems–a review of model predictive control (MPC);Afram;Building and Environment,2014

3. Gray-box modeling and validation of residential HVAC system for control system design;Afram;Applied Energy,2015

4. Supervisory model predictive controller (MPC) for residential HVAC systems: Implementation and experimentation on archetype sustainable house in Toronto;Afram;Energy and Buildings,2017

5. 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;Afram;Energy and Buildings,2017

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