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 <scp> ZrO <sub>2</sub> </scp> nanofluid

International Journal of Energy ResearchVolume 45, Issue 13 p. 18944-18956 RESEARCH ARTICLE 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 Andaç Batur Çolak, Corresponding Author Andaç Batur Çolak andacbaturcolak@hotmail.com orcid.org/0000-0001-9297-8134 Mechanical Engineering Department, Niğde Ömer Halisdemir University, Niğde, Turkey Correspondence Andaç Batur Çolak, Mechanical Engineering Department, Niğde Ömer Halisdemir University, Niğde 51240, Turkey. Email: andacbaturcolak@hotmail.comSearch for more papers by this author Andaç Batur Çolak, Corresponding Author Andaç Batur Çolak andacbaturcolak@hotmail.com orcid.org/0000-0001-9297-8134 Mechanical Engineering Department, Niğde Ömer Halisdemir University, Niğde, Turkey Correspondence Andaç Batur Çolak, Mechanical Engineering Department, Niğde Ömer Halisdemir University, Niğde 51240, Turkey. Email: andacbaturcolak@hotmail.comSearch for more papers by this author First published: 26 June 2021 https://doi.org/10.1002/er.6989Citations: 5Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Summary 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. Citing Literature Volume45, Issue1325 October 2021Pages 18944-18956 RelatedInformation