A novel comparative investigation of the effect of the number of neurons on the predictive performance of the artificial neural network: An experimental study on the thermal conductivity of ZrO2 nanofluid
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Wiley-Hindawi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In this study, the effect of the number of neurons on the predictive performance of artificial neural networks (ANN) has been investigated using experimental data. For this purpose, 6 different ANN have been developed by using a total of 60 experimental data of ZrO2/water nanofluid obtained from the literature. In ANN developed with the number of 5, 10, 15, 20, 25, and 30 neurons, all other parameters have been kept constant, and the effect of only the number of neurons on the prediction performance has been investigated. The performance of each ANN has been calculated separately and then their performance has been analyzed by comparing them with each other. As a consequence of the study, it has been seen that the model with the most ideal predictive performance has been developed with 5 neurons with an average error rate of 0.001%, and the highest margin of error the model has been developed with 15 neurons and had an error rate of 0.026%. In the light of the obtained data, it has been concluded that ANN are generally high performance predictive tools, and it is not possible to reach a standard correlation to regulate the number of neurons to be used in the optimization of ANN.
Açıklama
Anahtar Kelimeler
artificial neural network, nanofluid, neuron, thermal conductivity, zirconium oxide
Kaynak
International Journal of Energy Research
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
45
Sayı
13
