Thermal performance parameters estimation of hot box type solar cooker by using artificial neural network
Küçük Resim Yok
Tarih
2008
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier France-Editions Scientifiques Medicales Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Work to date has shown that Artificial Neural Network (ANN) has not been used for predicting thermal performance parameters of a solar cooker. The objective of this study is to predict thermal performance parameters such as absorber plate, enclosure air and pot water temperatures of the experimentally investigated box type solar cooker by using the ANN. Data set is obtained from the box type solar cooker which was tested under various experimental conditions. A feed-forward neural network based on back propagation algorithm was developed to predict the thermal performance of solar cooker with and without reflector. Mathematical formulations derived from the ANN model are presented for each predicting temperatures. The experimental data set consists of 126 values. These were divided into two groups, of which the 96 values were used for training/learning of the network and the rest of the data (30 values) for testing/validation of the network performance. The performance of the ANN predictions was evaluated by comparing the prediction results with the experimental results. The results showed a good regression analysis with the correlation coefficients in the range of 0.9950-0.9987 and mean relative errors (MREs) in the range of 3.92516-7.040% for the test data set. The regression coefficients indicated that the ANN model can successfully be used for the prediction of the thermal performance parameters of a box type solar cooker with a high degree of accuracy. (c) 2007 Elsevier Masson SAS. All rights reserved.
Açıklama
Anahtar Kelimeler
hot box type solar cooker, thermal performance parameters, artificial neural network
Kaynak
International Journal of Thermal Sciences
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
47
Sayı
2
