Modeling and optimization of HVAC systems using a dynamic neural network-Reference-Cited by-同舟云学术

Modeling and optimization of HVAC systems using a dynamic neural network

Published:2012-06 Issue:1 Volume:42 Page:241-250
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Kusiak Andrew,Xu Guanglin

Publisher

Elsevier BV

Subject

General Energy,Pollution,Mechanical Engineering,Building and Construction,Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Civil and Structural Engineering

Reference24 articles.

1. A review on building energy consumption information;Pérez-Lombard;Energy and Buildings,2008

2. Numerical prediction of indoor air humidity and its effect on indoor environment;Teodosiu;Building and Environment,2003

3. Evolutionary algorithms for multi-objective optimization in HVAC system control strategy;Nassif;Fuzzy Information,2004

4. Optimization of HVAC control system strategy using two objective genetic algorithm;Nassif;HVAC & Research,2005

5. A cost-effective operating strategy to reduce energy consumption in a HVAC system;Nassif;International Journal of Energy Research,2008

Cited by 126 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Efficient model-free control of chiller plants via cluster-based deep reinforcement learning;Journal of Building Engineering;2024-04

2. Emissions and mitigation potential of endocrine disruptors during outdoor exercise: Fate, transport, and implications for human health;Environmental Research;2023-11

3. Human-like Eco-driving Strategy of Electric Vehicle Considering Vehicle-to-everything Communication;2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI);2023-10-27

4. Optimal pressure prediction of R744 heat pump system based on PSO-BP-ANN model;Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023);2023-09-07

5. Investigations on machine learning-based control-oriented modeling using historical thermal data of buildings;Building and Environment;2023-09