engleski

The Prediction of the As-Cast Ductile Iron Impact Toughness by Using Thermal Analysis and Artificial Neural Networks

This paper presents the application of artificial neural network (ANN) in the foundry process. A two-layer feedforward neural network which is trained using backpropagation algorithm that updates weights and biases values according to gradient descent momentum and an adaptive learning rate (Backpropagation Neural Network- BPNN) have been established to predict the as- cast impact toughness of ductile iron (DI) using the thermal analysis (TA) parameters as inputs. The generalization property of the developed ANN is very good, which is confirmed by a very good accordance between the predicted and the targeted values of as-cast impact toughness on a new data set that was not included in the training data set.

ductile iron ; impact toughness ; artificial neural networks ; thermal analysis

Rad je kao predavanje prezentiran na skupu 47th Internationa Foundry Conference, održanom od 12.-14.09.2007., Portorož, Slovenija ; objavljen bez recenzije u Zborniku (ISSN 1318-9123) ; Ljubljana, Livarsko strokovno posvetovanje, 2007 ; str. 56-58.