Thermal behavior in solar distillation system using experimental and machine learning approach with scaled conjugated gradient algorithm
Yazarlar (3)
Dr. Öğr. Üyesi Yasin ÖZCAN Kastamonu Üniversitesi, Türkiye
Doç. Dr. Mehmet GÜRDAL Kastamonu Üniversitesi, Türkiye
Emrah Deniz Karabük Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Desalination (Q1) | ||
| Dergi ISSN | 0011-9164 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI | ||
| Makale Dili | İngilizce | Basım Tarihi | 05-2025 |
| Cilt / Sayı / Sayfa | 606 / 1 / – | DOI | 10.1016/j.desal.2025.118765 |
| Makale Linki | https://doi.org/10.1016/j.desal.2025.118765 | ||
| UAK Araştırma Alanları |
Isı Transferi
Akışkanlar Mekaniği
Termodinamik
|
||
| Özet |
| This study investigates the thermal dynamics of solar stills by combining experimental methods with machine learning techniques. The experimental setup consisted of two single-slope basin solar stills, from which temperature data were collected for the still, water, vapour, and glass surfaces. A machine learning model, specifically an Artificial Neural Network (ANN) using the Scaled Conjugate Gradient algorithm, was used to predict temperature variations throughout the distillation process. The ANN model achieved high prediction accuracy, with Coefficient of Determination (R2) above 0.99 for all temperature components. The study highlights the effectiveness of integrating machine learning into solar distillation systems, providing valuable insights for the design of more efficient technologies. These findings contribute to the understanding of sustainable water production and highlights the significant role of … |
| Anahtar Kelimeler |
| ANN | Machine learning | Solar distillation | Thermal behavior | Water scarcity |
Science Direct
Thermal behavior in solar distillation system using experimental and machine learning approach with scaled conjugated gradient algorithm
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 4 |
| Google Scholar | 4 |