Application of artificial neural network to predict the optimal start time for heating system in building-Reference-Cited by-同舟云学术

Application of artificial neural network to predict the optimal start time for heating system in building

Published:2003-10 Issue:17 Volume:44 Page:2791-2809
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Yang In-Ho,Yeo Myoung-Souk,Kim Kwang-Woo

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference16 articles.

1. ASHRAE. ASHRAE HANDBOOK: heating, ventilating, and air-conditioning applications. 1991. p. 38.2

2. Park, Cheol. An optimal start/stop algorithm for heating and cooling systems in buildings. National Bureau of Standards, US Department of Commerce; May 1983

3. Building energy management systems;Levermore;E&FN SPON,1992

4. Algorithm for predicting recovery time from night setback;Seem;ASHRAE Transaction,1989

5. Korea Institute of Construction Technology, A study on the HVAC system and lighting control conditions for building automation, 1987:53 [in Korean]

Cited by 168 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. Implementation and validation of optimal start control strategy for air conditioners and heat pumps;Applied Thermal Engineering;2024-12

2. Just-in-Time Morning Ramp-Up Implementation in Warehouses Enabled by Machine Learning-Based Predictive Modelling: Estimation of Achievable Energy Saving through Simulation;Energies;2024-09-03

3. Estimation of preheating time for building intermittent heating subject to changes in outdoor temperature and solar radiation;Energy and Buildings;2024-08

4. Supervised Learning based Iterative Learning Control Platform for Optimal HVAC Start-Stop in a Real Building Context;Case Studies in Thermal Engineering;2024-08

5. Influence of air-conditioning intermittent operation on the cooling load from opaque envelopes in residences;Case Studies in Thermal Engineering;2024-06