Özet
Türkiye's transition to electric vehicles driven by technological innovation, domestic electric vehicle (EV) efforts, and legislative incentives have become a visible reality. Short-term forecasting of monthly EV sales has become essential for all parties involved, such as automotive firms, infrastructure providers, energy planners and governments with the development of strategies on an annual or monthly basis. Many issues such as production, export, import, logistics, energy planning, infrastructure planning, installation and development of charging stations or other fields benefit from forecasting. Especially for fast developing countries such as Türkiye. In this study, two models are utilized for short-term forecasting EV sales in Türkiye; multi input deep assessment model (M-DAM) and long short-term memory (LSTM) model.
| Orijinal dil | İngilizce |
|---|---|
| Sayfa (başlangıç-bitiş) | 1094-1099 |
| Sayfa sayısı | 6 |
| Dergi | International Conference on Computer Science and Engineering, UBMK |
| Basın numarası | 2025 |
| DOI'lar | |
| Yayın durumu | Yayınlandı - 2025 |
| Etkinlik | 10th International Conference on Computer Science and Engineering, UBMK 2025 - Istanbul, Turkey Süre: 17 Eyl 2025 → 21 Eyl 2025 |
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Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur
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SKH 7 Erişilebilir ve Temiz Enerji
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SKH 9 Sanayi, Yenilikçilik ve Altyapı
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