Forecasting diurnal cooling energy load for institutional buildings using Artificial Neural Networks
C Deb, LS Eang, J Yang, M Santamouris - Energy and Buildings, 2016 - Elsevier
This study presents a methodology to forecast diurnal cooling load energy consumption for
institutional buildings using data driven techniques. The cases for three institutional …
institutional buildings using data driven techniques. The cases for three institutional …
Cooling load prediction for buildings using general regression neural networks
AE Ben-Nakhi, MA Mahmoud - Energy Conversion and Management, 2004 - Elsevier
General regression neural networks (GRNN) were designed and trained to investigate the
feasibility of using this technology to optimize HVAC thermal energy storage in public …
feasibility of using this technology to optimize HVAC thermal energy storage in public …
A study of the importance of occupancy to building cooling load in prediction by intelligent approach
SSK Kwok, EWM Lee - Energy Conversion and Management, 2011 - Elsevier
Building cooling load prediction is one of the key factors in the success of energy-saving
measures. Many computational models available in the industry today have been developed …
measures. Many computational models available in the industry today have been developed …
Novel dynamic forecasting model for building cooling loads combining an artificial neural network and an ensemble approach
Short-term load prediction, which forecasts a building's thermal load with a lead time ranging
from seconds to a few days, is essential for not only monitoring and controlling the system …
from seconds to a few days, is essential for not only monitoring and controlling the system …
Intelligent techniques for forecasting electricity consumption of buildings
The increasing trend in building sector's energy demand calls for reliable and robust energy
consumption forecasting models. This study aims to compare prediction capabilities of five …
consumption forecasting models. This study aims to compare prediction capabilities of five …
Application of optimized artificial intelligence algorithm to evaluate the heating energy demand of non-residential buildings at European level
A reliable preliminary forecast of heating energy demand of a building by using a detailed
dynamic simulation software typically requires an in-depth knowledge of the thermal …
dynamic simulation software typically requires an in-depth knowledge of the thermal …
Artificial neural networks applications in building energy predictions and a case study for tropical climates
M Yalcintas, S Akkurt - International journal of energy research, 2005 - Wiley Online Library
This study presents artificial neural network (ANN) methods in building energy use
predictions. Applications of the ANN methods in energy audits and energy savings …
predictions. Applications of the ANN methods in energy audits and energy savings …
Applied machine learning: Forecasting heat load in district heating system
Forecasting energy consumption in buildings is a key step towards the realization of
optimized energy production, distribution and consumption. This paper presents a data …
optimized energy production, distribution and consumption. This paper presents a data …
A long short-term memory artificial neural network to predict daily HVAC consumption in buildings
R Sendra-Arranz, A Gutiérrez - Energy and Buildings, 2020 - Elsevier
In this paper, the design and implementation process of an artificial neural network based
predictor to forecast a day ahead of the power consumption of a building HVAC system is …
predictor to forecast a day ahead of the power consumption of a building HVAC system is …
An intelligent approach to assessing the effect of building occupancy on building cooling load prediction
Building cooling load prediction is one of the key factors in the success of energy-saving
measures. Many computational models available in the industry have been developed from …
measures. Many computational models available in the industry have been developed from …