Leveraging digital technologies for circular economy in construction industry: a way forward

N Rodrigo, H Omrany, R Chang, J Zuo - Smart and Sustainable Built …, 2024 - emerald.com
Purpose This study aims to investigate the literature related to the use of digital technologies
for promoting circular economy (CE) in the construction industry. Design/methodology …

Restrictions and alternatives for the development data-based energy prediction models in buildings located in tropical climate: Literature review

J Cárdenas-Rangel, J Jaramillo-Ibarra… - Building and …, 2024 - Elsevier
Abstract–Prediction of energy consumption in buildings is the process that allows estimating
the amount of energy consumed in a specific future period. Typically, a predicted energy …

Cooling load prediction of a double-story terrace house using ensemble learning techniques and genetic programming with SHAP approach

C Cakiroglu, Y Aydın, G Bekdaş, U Isikdag… - Energy and …, 2024 - Elsevier
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 …

[HTML][HTML] Energy-efficiency measures to achieve zero energy buildings in tropical and humid climates

K Chung-Camargo, J González, T Solano, O Yuil… - 2023 - intechopen.com
Nearly and net zero energy buildings have been strongly studied in the global north, with
generally a temperate climate, thus focusing on energy-efficiency measures for such …

Deviation entropy-based dynamic multi-model ensemble interval prediction method for quantifying uncertainty of building cooling load

C Chen, J An, X Zhou, C Wang, H Li, D Yan - Energy and Buildings, 2024 - Elsevier
Interval prediction is a promising method that can reveal the uncertainty of building load and
has been shown to effectively manage building energy systems. Previous studies focused …

Building Energy Saving for Indoor Cooling and Heating: Mechanism and Comparison on Temperature Difference

J **ong, L Chen, Y Zhang - Sustainability, 2023 - mdpi.com
Reducing the heat transfer temperature difference via reasonable indoor temperature
determination and air conditioning system design is a confirmed building energy-saving …

[HTML][HTML] Modeling Soil Behavior with Machine Learning: Static and Cyclic Properties of High Plasticity Clays Treated with Lime and Fly Ash

G Bekdaş, Y Aydın, SM Nigdeli, İS Ünver, WW Kim… - Buildings, 2025 - mdpi.com
Soils may not always be suitable to fulfill their intended function. Soil improvement can be
achieved by mechanical or chemical methods, especially in transportation facilities. L and …

[HTML][HTML] Shear Wave Velocity Prediction with Hyperparameter Optimization

G Bekdaş, Y Aydın, U Işıkdağ, SM Nigdeli, D Hajebi… - Information, 2025 - mdpi.com
Shear wave velocity (Vs) is an important soil parameter to be known for earthquake-resistant
structural design and an important parameter for determining the dynamic properties of soils …

[PDF][PDF] Leveraging Feature Sets and Machine Learning for Enhanced Energy Load Prediction: A Comparative Analysis

FPS Almeida, M Castelli, N Côrte-Real - Emerging Science Journal, 2024 - run.unl.pt
Accurate cooling consumption forecasts are crucial for optimizing energy management,
storage, and overall efficiency in interconnected HVAC systems. Weather conditions …

Predicting Liquid Natural Gas Consumption via the Multilayer Perceptron Algorithm Using Bayesian Hyperparameter Autotuning

H Lee, W Cho, J Park, J Gu - Energies, 2024 - mdpi.com
Reductions in energy consumption and greenhouse gas emissions are required globally.
Under this background, the Multilayer Perceptron machine-learning algorithm was used to …