Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey
Yazarlar (5)
Ergun Uzlu Karadeniz Teknik Üniversitesi, Türkiye
Adem Akpınar Uludağ Üniversitesi, Türkiye
Hasan Tahsin Öztürk Karadeniz Teknik Üniversitesi, Türkiye
Doç. Dr. Sinan NACAR Karadeniz Teknik Üniversitesi, Türkiye
Murat Kankal Karadeniz Teknik Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | ENERGY (Q1) | ||
| Dergi ISSN | 0360-5442 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 05-2014 |
| Cilt / Sayı / Sayfa | 69 / 69 / 638–647 | DOI | 10.1016/j.energy.2014.03.059 |
| Özet |
| The primary objective of this study was to apply the ANN (artificial neural network) model with the ABC (artificial bee colony) algorithm to estimate annual hydraulic energy production of Turkey. GEED (gross electricity energy demand), population, AYT (average yearly temperature), and energy consumption were selected as independent variables in the model. The first part of the study compared ANN-ABC model performance with results of classical ANN models trained with the BP (back propagation) algorithm. Mean square and relative error were applied to evaluate model accuracy. The test set errors emphasized positive differences between the ANN-ABC and classical ANN models. After determining optimal configurations, three different scenarios were developed to predict future hydropower generation values for Turkey. Results showed the ANN-ABC method predicted hydroelectric generation better than the … |
| Anahtar Kelimeler |
| Artificial bee colony algorithm | Hydropower generation | Neural networks | Turkey |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 83 |
| Google Scholar | 128 |