Wind speed estimation for missing wind data with three different backpropagation algorithms
Yükleniyor...
Tarih
2012
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Sila Science
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, wind data acquired from Tokat province located in the Central Black Sea section of the Black Sea region of Turkey were used to estimate wind speed by using artificial neural networks (ANN). A 3-layer feedback network was designed for wind speed modeling with MATLAB Neural Network Toolbox. Data used were acquired from State Meteorological station taken from a height of 10 meters. By using daily average wind speed data of Tokat province in 2010, ANN feedback network algorithms were used in order to recover any missing wind speed data. ANN feedback model Levenberg - Marquardt (LM) learning algorithm, the gradient - Descent (GD) learning algorithm and Resilient (RPROP) learning algorithm were used for randomly selected three data for each month and root mean square error (RMSE) and mean square error (MSE) values were calculated.
Açıklama
LUY, Murat/0000-0002-2378-0009;
Anahtar Kelimeler
Wind speed prediction, Neural networks, Backpropagation, Levenberg-Marquardt, Resilient, Gradient Descent
Kaynak
Energy Education Science And Technology Part A-Energy Science And Research
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
30
Sayı
1
Künye
closedAccess
