An experimental study on the comparative analysis of the effect of the number of data on the error rates of artificial neural networks

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dc.authoridColak, Andac Batur/0000-0001-9297-8134
dc.contributor.authorColak, Andac Batur
dc.date.accessioned2024-11-07T13:24:59Z
dc.date.available2024-11-07T13:24:59Z
dc.date.issued2021
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractIn this study, the effect of the amount of data used in the design of artificial neural networks (ANNs) on the predictive accuracy of ANNs was investigated. Five different ANNs were designed using the experimentally measured specific heat data of the Al2O3/water nanofluid prepared at volumetric concentrations of 0.0125, 0.025, 0.05, 0.1 and 0.2 using the Al(2)O(3)nanoparticle. The developed ANN is a multi-layer perceptron, feedforward and backpropagation model. In each ANN with 15 neurons in the hidden layer, the volumetric concentration (phi) and temperature (T) values were nominated as input layer factors and the specific heat value was estimated as the output value. With the aim of survey the effect of the amount of data on the predicted results of the ANN, a different amount of datasets were used in each developed ANN. In this context, in total 260 data were used in the Model 1 ANN. Subsequently, the total amount of data was reduced by 20% in each developed neural network and 55 data were used in the ANN named Model#5. The results obtained show that ANNs are highly talented of predicting the specific heat values of Al2O3/water nanofluid. However, in the comparisons, it was evaluated that the amount of data used had a share on the prediction performance of the ANN and that the decrease in the amount of data with the prediction performance of the ANN decreased.
dc.identifier.doi10.1002/er.5680
dc.identifier.endpage500
dc.identifier.issn0363-907X
dc.identifier.issn1099-114X
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85087682657
dc.identifier.scopusqualityQ1
dc.identifier.startpage478
dc.identifier.urihttps://doi.org/10.1002/er.5680
dc.identifier.urihttps://hdl.handle.net/11480/14448
dc.identifier.volume45
dc.identifier.wosWOS:000547170000001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherWiley
dc.relation.ispartofInternational Journal of Energy Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241106
dc.subjectartificial neural network
dc.subjecterror rates
dc.subjectnanofluid
dc.subjectnumber of data
dc.subjectspecific heat
dc.titleAn experimental study on the comparative analysis of the effect of the number of data on the error rates of artificial neural networks
dc.typeArticle

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