The optimized artificial neural network model with Levenberg-Marquardt algorithm for global solar radiation estimation in Eastern Mediterranean Region of Turkey
[ X ]
Tarih
2016
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier Sci Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
An accurate knowledge on global solar radiation is particularly required for proper placement and design of solar energy conversion systems. While the meteorological data are measured at most of the weather stations, global solar radiation measurement is not always performed due to high cost of the measurement devices and their operation and maintenance requirements. Therefore, several linear, non-linear and soft computing models are developed to estimate the solar radiation owing to being more economical when compared to installing pyranometers and these models provide satisfactory results. However, it is crucial to choose the most appropriate model for a specific purpose and region. The primary objective of this study is to optimize the performance of the artificial neural network model in order to realize an efficient estimation of solar radiation for Eastern Mediterranean Region of Turkey. Estimation performances are discussed for different structures of neural network by taking into account the number and quality of input features, learning algorithms, number of hidden neurons, correlation between network outputs and targets, and statistical error analysis methods. The presented model indicates that the artificial neural network models illustrate promising in the estimation of monthly mean daily global solar radiation by using commonly available data. In order to indicate the superiority of the performance of the model, it is evaluated with various test years, which are not used for training stage of the model. The presented model provides superior relationship between the estimated and measured values. The test results showed that the coefficient of determination and mean absolute percentage error between the optimized artificial neural network estimations and measured values for testing datasets are higher than 99% and %5, respectively. 2015 Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
Global solar radiation estimation, Artificial neural network, Eastern Mediterranean Region
Kaynak
Journal of Cleaner Production
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
116
