Open Access
| Issue |
E3S Web Conf.
Volume 661, 2025
The 18th Thai Society of Agricultural Engineering International Conference “Climate Resilient Agriculture for Asia” (TSAE 2025)
|
|
|---|---|---|
| Article Number | 04012 | |
| Number of page(s) | 5 | |
| Section | Energy and Environment | |
| DOI | https://doi.org/10.1051/e3sconf/202566104012 | |
| Published online | 13 November 2025 | |
- S.A. Kalogirou. Applications of artificial neural networks in energy systems. Energy Conversion and Management. 40(10), 1073-1087 (1999) [Google Scholar]
- P. Zhao. et al., A machine learning and CFD modeling hybrid approach for predicting real-time heat transfer during cokemaking processes. Fuel. 373(1), 132273 (2024) [Google Scholar]
- Md. M. Hasan, et. al., Artificial Neural Network Modeling for Predicting Thermal Conductivity of EG/Water-Based CNC Nanofluid for Engine Cooling Using Different Activation Functions. Frontiers in Heat and Mass Transfer. 22 (2), 537–556 (2024) [Google Scholar]
- W. M. Shaban, et al., Optimizing photovoltaic thermal solar systems efficiency through advanced artificial intelligence driven thermal management techniques. Applied Thermal Engineering. 247, 123029 (2024) [Google Scholar]
- A. Refahi. et al., Implementation of a double layer of PCM integrated into the building exterior walls for reducing annual energy consumption: Effect of PCM wallboards position. Journal of Energy Storage. 82, 110556 (2024) [Google Scholar]
- Y. Boutahri, et. al., Machine learning-based predictive model for thermal comfort and energy optimization in smart buildings. Results in Engineering. 22, 102148 (2024) [Google Scholar]
- L. Zhang. et al., Artificial intelligence in renewable energy: A comprehensive bibliometric analysis. Energy Reports. 8, 14072-14088 (2022) [Google Scholar]
- Elsevier. (2024). Scopus Content Coverage Guide. [Google Scholar]
- J. Zhu. et al., Hybrid thermal load prediction model for the regional built environment based on random forest feature screening. Energy and Buildings. 344, 115987 (2025) [Google Scholar]
- P. Li. et al., Physics-informed neural network for real-time thermal modeling of large-scale borehole thermal energy storage systems. Energy. 315, 134344 (2025) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.