Classification of Wheat Types by Artificial Neural Network

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dc.contributor.authorYasar, Ali
dc.contributor.authorKaya, Esra
dc.contributor.authorSarıtas, Ismail
dc.date.accessioned2020-03-26T19:09:26Z
dc.date.available2020-03-26T19:09:26Z
dc.date.issued2016
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn this study, the types of wheat seeds are classified using present data with artificial neural network (ANN) approach. Seven inputs, one hidden layer with 10 neurons and one output has been used for the ANN in our system. All of these parameters were real-valued continuous. The wheat varieties, Kama, Rosa and Canadian, characterized by measurement of main grain geometric features obtained by X-ray technique, have been analyzed. Results indicate that the proposed method is expected to be an effective method for recognizing wheat varieties. These seven input parameters reaches the 10-neurons hidden layer of the network and they are processed and then classified with an output. The classification process of 210 units of data using ANN is determined to make a successful classification as much as the actual data set. The regression results of the classification process is quite high. It is determined that the training regression R is 0,9999, testing regression is 0,99785 and the validation regression is 0,9947, respectively. Based on these results, classification process using ANN has been seen to achieve outstanding successen_US
dc.identifier.citationYasar A., Kaya E., Sarıtas I. (2016). Classification of Wheat Types by Artificial Neural Network. International Journal of Intelligent Systems and Applications in Engineering, 4(1), 12-15.
dc.identifier.endpage15en_US
dc.identifier.issn2147-6799en_US
dc.identifier.issn2147-6799en_US
dc.identifier.issue1en_US
dc.identifier.startpage12en_US
dc.identifier.urihttp://www.trdizin.gov.tr/publication/paper/detail/TWpFeU9UTTVPUT09
dc.identifier.urihttps://hdl.handle.net/20.500.12395/33027
dc.identifier.volume4en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Intelligent Systems and Applications in Engineeringen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectBilgisayar Bilimlerien_US
dc.subjectYapay Zekaen_US
dc.titleClassification of Wheat Types by Artificial Neural Networken_US
dc.typeArticleen_US

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