Prediction of Layer Thickness in Molten Borax Bath with Genetic Evolutionary Programming

dc.creator	Taylan, Fatih
dc.date	2011-02-28T22:00:00Z
dc.date.accessioned	2020-10-06T11:22:04Z
dc.date.available	2020-10-06T11:22:04Z
dc.identifier	bed7e1d4-409a-4d08-8b64-d48538c1781f
dc.identifier	10.1515/zna-2011-3-408
dc.identifier	https://avesis.sdu.edu.tr/publication/details/bed7e1d4-409a-4d08-8b64-d48538c1781f/oai
dc.identifier.uri	http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/70919
dc.description	In this study, the vanadium carbide coating in molten borax bath process is modeled by evolutionary genetic programming (GEP) with bath composition (borax percentage, ferro vanadium (Fe-V) percentage, boric acid percentage), bath temperature, immersion time, and layer thickness data. Five inputs and one output data exist in the model. The percentage of borax, Fe-V, and boric acid, temperature, and immersion time parameters are used as input data and the layer thickness value is used as output data. For selected bath components, immersion time, and temperature variables, the layer thicknesses are derived from the mathematical expression. The results of the mathematical expressions are compared to that of experimental data; it is determined that the derived mathematical expression has an accuracy of 89%.
dc.language	eng
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Prediction of Layer Thickness in Molten Borax Bath with Genetic Evolutionary Programming
dc.type	info:eu-repo/semantics/article

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