Application of artificial intelligence for prediction, optimization, and control of thermal energy storage systems

AG Olabi, AA Abdelghafar, HM Maghrabie… - Thermal Science and …, 2023 - Elsevier
Energy storage is one of the core concepts demonstrated incredibly remarkable
effectiveness in various energy systems. Energy storage systems are vital for maximizing the …

A review of climate adaptation of phase change material incorporated in building envelopes for passive energy conservation

T Yang, Y Ding, B Li, AK Athienitis - Building and Environment, 2023 - Elsevier
Phase change materials (PCMs) incorporated into building envelopes store large amount of
latent heat within a narrow temperature range, regulating heat flow between indoor and …

[HTML][HTML] A review of grout materials in geothermal energy applications

M Mahmoud, M Ramadan, K Pullen… - International Journal of …, 2021 - Elsevier
Ground heat exchangers are surrounded by grout material, making it one of the most
important components in geothermal energy applications since it significantly affects the …

An RF and LSSVM–NSGA-II method for the multi-objective optimization of high-performance concrete durability

H Chen, T Deng, T Du, B Chen, MJ Skibniewski… - Cement and Concrete …, 2022 - Elsevier
The development of cost-effective high-performance concrete (HPC) has long been a focus
of concrete research. Multiple objectives are required for the design of the HPC mix …

Optimization of high-performance concrete mix ratio design using machine learning

B Chen, L Wang, Z Feng, Y Liu, X Wu, Y Qin… - … Applications of Artificial …, 2023 - Elsevier
High-durability concrete is required in extremely cold or ocean environments, making the
design of concrete mixes highly important and complicated. In this study, a hybrid intelligent …

Optimization of annual electricity consumption costs and the costs of insulation and phase change materials in the residential building using artificial neural network …

M Baghoolizadeh, SAHH Dehkordi… - Journal of Energy …, 2023 - Elsevier
Overuse of energy resources (especially in residential building) has been one of the most
important issues in recent decades. Researchers have often focused on the use of PCM …

Forecasting energy demand of PCM integrated residential buildings: A machine learning approach

M Zhussupbekov, SA Memon, SA Khawaja… - Journal of Building …, 2023 - Elsevier
Forecasting energy demand has become an essential element for energy stakeholders in
planning and reducing the energy consumption of buildings. Machine learning techniques …

Integrated multi-stage sensitivity analysis and multi-objective optimization approach for PCM integrated residential buildings in different climate zones

A Saurbayeva, SA Memon, J Kim - Energy, 2023 - Elsevier
The early design stage provides the greatest opportunities to achieve energy-efficient
buildings; however, designers require relevant performance data to manage …

Energy consumption predictions by genetic programming methods for PCM integrated building in the tropical savanna climate zone

K Nazir, SA Memon, A Saurbayeva, A Ahmad - Journal of Building …, 2023 - Elsevier
The development of energy-efficient buildings by considering early-stage design parameters
can help reduce buildings' energy consumption. Machine learning tools are getting popular …

Multi-objective optimization of setpoint temperature of thermostats in residential buildings

H Bagheri-Esfeh, MR Dehghan - Energy and Buildings, 2022 - Elsevier
Determination of the optimum setpoint temperature of thermostats in various climates is a
problem in air conditioning of residential buildings. In this paper, a new method is developed …