The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network

Serkan Şenkal; Cem Emeksiz

doi:10.47897/bilmes.1406384

TR EN

The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network

Öz

This study investigates the effect of data decomposition to improve the performance of artificial neural networks (ANNs), widely used in wind speed forecasting in the wind energy sector. Artificial neural networks are essential tools for planning and optimizing the daily generation of wind power plants. However, prediction errors can lead to significant problems in power generation and energy grid management. The results show that data decomposition substantially affects the wind speed forecasting performance of neural networks. These findings are essential for researchers and industry professionals interested in developing more accurate forecasting models for power generation planning and management in the wind energy sector. By integrating artificial neural networks and data disaggregation methods, the study stands out as an essential step forward to improve the accuracy of wind speed forecasts and optimize the efficiency of wind energy facilities.

Anahtar Kelimeler

Wind speed estimation, artificial neural networks, data decomposition

Kaynakça

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Ayrıntılar

Birincil Dil

Türkçe

Konular

Rüzgar Enerjisi Sistemleri, Yenilenebilir Enerji Sistemleri

Bölüm

Araştırma Makalesi

Yazarlar

Serkan Şenkal ^*
0000-0002-4571-3923
Türkiye

Cem Emeksiz
0000-0002-4817-9607
Türkiye

Yayımlanma Tarihi

31 Aralık 2023

Gönderilme Tarihi

18 Aralık 2023

Kabul Tarihi

29 Aralık 2023

Yayımlandığı Sayı

Yıl 2023 Cilt: 7 Sayı: 2

DOI

https://doi.org/10.47897/bilmes.1406384

IZ

https://izlik.org/JA89RU47SF

APA

Şenkal, S., & Emeksiz, C. (2023). The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network. International Scientific and Vocational Studies Journal, 7(2), 213-223. https://doi.org/10.47897/bilmes.1406384

AMA

1.Şenkal S, Emeksiz C. The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network. ISVOS. 2023;7(2):213-223. doi:10.47897/bilmes.1406384

Chicago

Şenkal, Serkan, ve Cem Emeksiz. 2023. “The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network”. International Scientific and Vocational Studies Journal 7 (2): 213-23. https://doi.org/10.47897/bilmes.1406384.

EndNote

Şenkal S, Emeksiz C (01 Aralık 2023) The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network. International Scientific and Vocational Studies Journal 7 2 213–223.

IEEE

[1]S. Şenkal ve C. Emeksiz, “The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network”, ISVOS, c. 7, sy 2, ss. 213–223, Ara. 2023, doi: 10.47897/bilmes.1406384.

ISNAD

Şenkal, Serkan - Emeksiz, Cem. “The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network”. International Scientific and Vocational Studies Journal 7/2 (01 Aralık 2023): 213-223. https://doi.org/10.47897/bilmes.1406384.

JAMA

1.Şenkal S, Emeksiz C. The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network. ISVOS. 2023;7:213–223.

MLA

Şenkal, Serkan, ve Cem Emeksiz. “The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network”. International Scientific and Vocational Studies Journal, c. 7, sy 2, Aralık 2023, ss. 213-2, doi:10.47897/bilmes.1406384.

Vancouver

1.Serkan Şenkal, Cem Emeksiz. The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network. ISVOS. 01 Aralık 2023;7(2):213-2. doi:10.47897/bilmes.1406384

Cited By

A comparative analysis of iterative and variational decomposition strategies for wind speed forecasting: LMD and VMD

International Journal of Energy Studies

https://doi.org/10.58559/ijes.1847604

Forecasting Wind Speed with Autoregressive and Long-Short Term Memory Neural Network Models

Journal of AI

https://doi.org/10.61969/jai.1789834

ULUSLARARASI BİLİMSEL VE MESLEKİ ÇALIŞMALAR DERGİSİ, Creative Commons Atıf-GayrıTicari 4.0 Uluslararası (CC BY-NC 4.0) lisansı ile yayınlamasına izin verir. Creative Commons Atıf-GayrıTicari 4.0 Uluslararası (CC BY-NC 4.0) lisansı, eserin ticari kullanım dışında her boyut ve formatta paylaşılmasına, kopyalanmasına, çoğaltılmasına ve orijinal esere uygun şekilde atıfta bulunmak kaydıyla yeniden düzenleme, dönüştürme ve eserin üzerine inşa etme dâhil adapte edilmesine izin verir.

The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network

Öz

Anahtar Kelimeler

The Effect of Data Decomposition on Prediction Performance in Wind Speed Prediction with Artificial Neural Network

Öz

Anahtar Kelimeler

Kaynakça

Ayrıntılar

Birincil Dil

Konular

Bölüm

Yazarlar

Yayımlanma Tarihi

Gönderilme Tarihi

Kabul Tarihi

Yayımlandığı Sayı

DOI

IZ

Kaynak Göster

Cited By

A comparative analysis of iterative and variational decomposition strategies for wind speed forecasting: LMD and VMD

Forecasting Wind Speed with Autoregressive and Long-Short Term Memory Neural Network Models