T. Gurgenc And O. ALTAY, "Surface roughness prediction of wire electric discharge machining (WEDM)-machined AZ91D magnesium alloy using multilayer perceptron, ensemble neural network, and evolving product-unit neural network," Materialpruefung/Materials Testing , vol.64, no.3, pp.350-362, 2022
Gurgenc, T. And ALTAY, O. 2022. Surface roughness prediction of wire electric discharge machining (WEDM)-machined AZ91D magnesium alloy using multilayer perceptron, ensemble neural network, and evolving product-unit neural network. Materialpruefung/Materials Testing , vol.64, no.3 , 350-362.
Gurgenc, T., & ALTAY, O., (2022). Surface roughness prediction of wire electric discharge machining (WEDM)-machined AZ91D magnesium alloy using multilayer perceptron, ensemble neural network, and evolving product-unit neural network. Materialpruefung/Materials Testing , vol.64, no.3, 350-362.
Gurgenc, Turan, And OSMAN ALTAY. "Surface roughness prediction of wire electric discharge machining (WEDM)-machined AZ91D magnesium alloy using multilayer perceptron, ensemble neural network, and evolving product-unit neural network," Materialpruefung/Materials Testing , vol.64, no.3, 350-362, 2022
Gurgenc, Turan And ALTAY, OSMAN. "Surface roughness prediction of wire electric discharge machining (WEDM)-machined AZ91D magnesium alloy using multilayer perceptron, ensemble neural network, and evolving product-unit neural network." Materialpruefung/Materials Testing , vol.64, no.3, pp.350-362, 2022
Gurgenc, T. And ALTAY, O. (2022) . "Surface roughness prediction of wire electric discharge machining (WEDM)-machined AZ91D magnesium alloy using multilayer perceptron, ensemble neural network, and evolving product-unit neural network." Materialpruefung/Materials Testing , vol.64, no.3, pp.350-362.
@article{article, author={Turan Gurgenc And author={OSMAN ALTAY}, title={Surface roughness prediction of wire electric discharge machining (WEDM)-machined AZ91D magnesium alloy using multilayer perceptron, ensemble neural network, and evolving product-unit neural network}, journal={Materialpruefung/Materials Testing}, year=2022, pages={350-362} }