The prediction of the microstructure constituents of spheroidal graphite cast iron by using thermal analysis and artificial neural networks (CROSBI ID 150184)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Glavaš, Zoran ; Unkić, Faruk ; Lisjak, Dragutin
engleski
The prediction of the microstructure constituents of spheroidal graphite cast iron by using thermal analysis and artificial neural networks
This paper presents the application of artificial neural networks in the production process of spheroidal graphite cast iron. Backpropagation neural networks have been established to predict the microstructure constituents (ferrite content, pearlite content, nodule count and nodularity) of spheroidal graphite cast iron using the thermal analysis parameters as inputs. Generalization properties of the developed artificial neural networks are very good, which is confirmed by a very good accordance between the predicted and the targeted values of the microstructure constituents on a new data set that was not included in the training data set.
spheroidal graphite cast iron ; microstructure constituents ; thermal analysis ; artificial neural networks
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