Pregled bibliografske jedinice broj: 72247
DETERMINING OF STEEL CARBURIZING PARAMETERS USING NEURAL NETWORKS
DETERMINING OF STEEL CARBURIZING PARAMETERS USING NEURAL NETWORKS // INTEGRATION OF HEAT TREATMENT AND SURFACE ENGINEERING IN THE MANUFACTURE OF ENGINEERING COMPONENTS / Božidar Liščić (ur.).
Zagreb: Hrvatsko društvo za toplinsku obradu i inženjerstvo površina, 2001. str. 407-413 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
DETERMINING OF STEEL CARBURIZING PARAMETERS USING NEURAL NETWORKS
Autori
Dragutin Lisjak, Božidar Matijević
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
INTEGRATION OF HEAT TREATMENT AND SURFACE ENGINEERING IN THE MANUFACTURE OF ENGINEERING COMPONENTS
/ Božidar Liščić - Zagreb : Hrvatsko društvo za toplinsku obradu i inženjerstvo površina, 2001, 407-413
Skup
8th SEMINAR OF THE INTERNATIONAL FEDERATION FOR HEAT TREATMENT AND SURFACE ENGINERRING IFHTSE 2001
Mjesto i datum
Dubrovnik, Hrvatska, 12.09.2001. - 14.09.2001
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
carburizing; carbomaag; neural networks
Sažetak
The paper discusses application of neural networks for calculating the laws of complex processes, among which are carbon diffusion processes in steel carburizing. For determining of technological carburizing parameters, which results in required course of carbon curves in the carburized layer, empirical and mathematical model for Carbomaag carburizing process are presented, which are proven in practice. The results of empirical carburizing model were used as a neural network training set and compared with the results of computer simulation of mathematical model. Comparison of results of carburizing provided by neural network with empirical and mathematical model shows good correspondence. It is considered that more experiments and using newer sets of experimental data in training of neural network would provide better solutions i.e. deficiencies of empirical and theoretical models would be avoided.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo