Makale detayı · 2022 · article
Electricity Load Forecasting Using Deep Learning and Novel Hybrid Models
Veri kaynağı ayrımı
- YÖKSİSYÖKSİS makale kaydı
- YÖKSİS dergi adıSakarya University Journal of Science
- Katalog eşleşmesi (ISSN)Sakarya University Journal of Science
- OpenAlexOpenAlex zenginleştirmesi (özet, atıf, konular)
- Semantic Scholaratıf sayısı (OpenAlex ile birleştirilmez)
Özet
Load forecasting is an essential task which is executed by electricity retail companies. By predicting the demand accurately, companies can prevent waste of resources and blackouts. Load forecasting directly affect the financial of the company and the stability of the Turkish Electricity Market. This study is conducted with an electricity retail company, and main focus of the study is to build accurate models for load. Datasets with novel features are preprocessed, then deep learning models are built in order to achieve high accuracy for these problems. Furthermore, a novel method for solving regression problems with classification approach (discretization) is developed for this study. In order to obtain more robust model, an ensemble model is developed and the success of individual models are evaluated in comparison to each other.
Konular
Atıflar
OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.
5atıfOpenAlex · cited_by_count (önbellek / veritabanı)
Yerel katalogda bu makaleye atıf yapan 4 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).
- 2023 KOSGEB Ar-Ge ve İnovasyon Desteklerinin İmalatçı Firmalar Üzerindeki Etkilerinin Araştırılması: Kayseri İli ÖrneğiAtıf 2 · OpenAlex
- 2023 KOSGEB Ar-Ge ve İnovasyon Desteklerinin İmalatçı Firmalar Üzerindeki Etkilerinin Araştırılması: Kayseri İli ÖrneğiAtıf 2 · OpenAlex
- 2024 Comparison of Deep Learning and Yolov8 Models for Fox Detection Around the HenhouseAtıf 1 · OpenAlex
- 2023 Analysis of System Marginal Price in the Turkish Electricity MarketAtıf 0 · OpenAlex