Systematic review of deep learning and machine learning for building energy

S Ardabili, L Abdolalizadeh, C Mako, B Torok… - Frontiers in Energy …, 2022 - frontiersin.org
The building energy (BE) management plays an essential role in urban sustainability and
smart cities. Recently, the novel data science and data-driven technologies have shown …

[HTML][HTML] Application of Nanofluids in CO2 Absorption: A Review

B Aghel, S Janati, F Alobaid, A Almoslh, B Epple - Applied Sciences, 2022 - mdpi.com
The continuous release of CO2 into the atmosphere as a major cause of increasing global
warming has become a growing concern for the environment. Accordingly, CO2 absorption …

[HTML][HTML] Electrical efficiency of the photovoltaic/thermal collectors cooled by nanofluids: Machine learning simulation and optimization by evolutionary algorithm

Y Cao, E Kamrani, S Mirzaei, A Khandakar, B Vaferi - Energy Reports, 2022 - Elsevier
Abstract Photovoltaic/thermal (PV/T) are high-tech devices to transform solar radiation into
electrical and thermal energies. Nano-coolants are recently considered to enhance the …

Numerical investigation of carbon dioxide capture using nanofluids via machine learning

L Feng, J Zhu, Z Jiang - Journal of Cleaner Production, 2024 - Elsevier
Using nanofluids to capture CO 2 is a promising method of reducing emissions. The goal of
this study was to develop models that could forecast how well water-based nanofluids would …

Optimizing the thermal performance of the thermosyphon heat pipe for energy saving with graphene oxide nanofluid

K Afsari, MRS Emami, S Zahmatkesh, JJ Klemeš… - Energy, 2023 - Elsevier
A thermosyphon heat pipe (THP) involves a vacuum tube with a specific quantity of liquid.
Due to its simplicity of design and structure, THP has many applications in heat recovery and …

A novel machine learning-based framework for the water quality parameters prediction using hybrid long short-term memory and locally weighted scatterplot …

A Dodig, E Ricci, G Kvascev… - Journal of …, 2024 - iwaponline.com
Water quality prediction is crucial for effective river stream management. Dissolved oxygen,
conductivity and chemical oxygen demand are vital chemical parameters for water quality …

Potential application of metal-organic frameworks (MOFs) for hydrogen storage: Simulation by artificial intelligent techniques

Y Cao, HA Dhahad, SG Zare, N Farouk, AE Anqi… - International Journal of …, 2021 - Elsevier
Metal-organic frameworks are a new class of materials for hydrogen adsorption/storage
applications. The hydrogen storage capacity of this structure is typically related to pressure …

[HTML][HTML] A TLBO-Tuned neural processor for predicting heating load in residential buildings

K Almutairi, S Algarni, T Alqahtani, H Moayedi… - Sustainability, 2022 - mdpi.com
Recent studies have witnessed remarkable merits of metaheuristic algorithms in
optimization problems. Due to the significance of the early analysis of the thermal load in …

Synthesis, characterization, conductivity, and gas‐sensing performance of copolymer nanocomposites based on copper alumina and poly(aniline‐co‐pyrrole)

S Sankar, MT Ramesan - Polymer Engineering & Science, 2022 - Wiley Online Library
A series of copolymer nanocomposites based on poly (aniline‐co‐pyrrole)(PANI‐co‐PPy)
with different contents of copper alumina (Cu‐Al2O3) nanoparticles were synthesized by …

Thermal, optical and temperature-dependent electrical properties of poly(aniline-co-pyrrole)/copper alumina nanocomposites for optoelectronic devices

S Sankar, MT Ramesan - Journal of Thermal Analysis and Calorimetry, 2022 - Springer
The article deals with the investigation of structural, thermal and temperature-dependent
alternating current (AC) parameters of hetero-structures generated by the reinforcement of …