Prediction of cooling load of tropical buildings with machine learning
Cooling load refers to the amount of energy to be removed from a space (or consumed) to
bring that space to an acceptable temperature or to maintain the temperature of a space at …
bring that space to an acceptable temperature or to maintain the temperature of a space at …
Re-evaluation of building cooling load prediction models for use in humid subtropical area
For buildings in subtropical area with negligible heating load, prediction of short term
building cooling load is of critical importance to achieve the energy saving target. However …
building cooling load is of critical importance to achieve the energy saving target. However …
Short-term cooling load prediction for office buildings based on feature selection scheme and stacking ensemble model
W Gao, X Huang, M Lin, J Jia, Z Tian - Engineering Computations, 2022 - emerald.com
Purpose The purpose of this paper is to target on designing a short-term load prediction
framework that can accurately predict the cooling load of office buildings …
framework that can accurately predict the cooling load of office buildings …
Prediction and optimization of heating and cooling loads in a residential building based on multi-layer perceptron neural network and different optimization algorithms
Y Xu, F Li, A Asgari - Energy, 2022 - Elsevier
Since cooling and heating loads are regarded as significant parameters to examine the
energy performance of buildings, the need to predict and analyze them for the residential …
energy performance of buildings, the need to predict and analyze them for the residential …
Cooling load prediction of a double-story terrace house using ensemble learning techniques and genetic programming with SHAP approach
Since the cooling systems used in buildings in hot climates account for a significant portion
of the energy consumption, it is very important for both economy and environment to …
of the energy consumption, it is very important for both economy and environment to …
Forecasting heating and cooling loads in residential buildings using machine learning: A comparative study of techniques and influential indicators
B Mehdizadeh Khorrami, A Soleimani… - Asian Journal of Civil …, 2024 - Springer
Residential buildings are a significant source of energy consumption and greenhouse gas
emissions, making it crucial to accurately predict their energy demand for reducing their …
emissions, making it crucial to accurately predict their energy demand for reducing their …
A short-term building cooling load prediction method using deep learning algorithms
Short-term building cooling load prediction is the essential foundation for many building
energy management tasks, such as fault detection and diagnosis, demand-side …
energy management tasks, such as fault detection and diagnosis, demand-side …
Energy efficiency prediction using artificial neural network
AJ Khalil, AM Barhoom, BS Abu-Nasser, MM Musleh… - 2019 - philpapers.org
Buildings energy consumption is growing gradually and put away around 40% of total
energy use. Predicting heating and cooling loads of a building in the initial phase of the …
energy use. Predicting heating and cooling loads of a building in the initial phase of the …
Developing machine-learning meta-models for high-rise residential district cooling in hot and humid climate
Cooling accounts for a significant amount of energy consumption in hot and humid climates,
and district cooling is an energy-efficient solution. During its planning stage, an accurate and …
and district cooling is an energy-efficient solution. During its planning stage, an accurate and …
[PDF][PDF] Prediction of heating and cooling load to improve energy efficiency of buildings using machine learning techniques
J Srihari, B Santhi - J. Mech. Cont. Math. Sci, 2018 - jmcms.s3.amazonaws.com
Global warming has been a severe threat to humanityand greenhouse gases emitted from
power plants is one of the major causes of global warming. In this paper, we use machine …
power plants is one of the major causes of global warming. In this paper, we use machine …