Determining the carrot volume via radius and length using ANN

dc.contributor.authorÖrnek, Mustafa Nevzat
dc.contributor.authorKahramanlı, Humar
dc.date.accessioned2020-03-26T19:45:20Z
dc.date.available2020-03-26T19:45:20Z
dc.date.issued2018
dc.departmentSelçuk Üniversitesi, Teknoloji Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractIn this study a total of 464 carrots were taken from Kaşınhanı, where the most carrots in Turkey are produced. The radiuses with an interval of 5 cm, length and volume of each carrot were measured and recorded. Three different Artificial Neural Network models: BP, LM and PUNN were designed for predicting the carrot volume. To assess the success of the system, statistical measures such as Root Mean Squared Error, Mean Absolute Error and R2 were used. The results showed that all three methods are successful in this problem, while LM and PUNN seems bit better.en_US
dc.identifier.citationÖrnek, M. N., Kahramanlı, H. (2018). Determining the Carrot Volume Via Radius and Length Using ANN. International Journal of Intelligent Systems and Applications in Engineering, 6(2), 165-169.
dc.identifier.endpage169en_US
dc.identifier.issn2147-6799en_US
dc.identifier.issn2147-6799en_US
dc.identifier.issue2en_US
dc.identifier.startpage165en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/36024
dc.identifier.volume6en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.institutionauthorÖrnek, Mustafa Nevzat
dc.institutionauthorKahramanlı, Humar
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/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectBilgisayar Bilimlerien_US
dc.subjectYapay Zekaen_US
dc.titleDetermining the carrot volume via radius and length using ANNen_US
dc.typeArticleen_US
dcterms.subjectcarrots physical properties

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