Metalurgija, Vol. 47 No. 4, 2008.
Izvorni znanstveni članak
Genetic programming and cae neural networks approach for prediction of the bending capability of ZnTiCu sheets
R. Turk
; Faculty of Natural Sciences, Ljubljana, Slovenia
I. Peruš
; Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia
M. Kovačič
; Štore steel, Ltd, Štore, Slovenia
G. Kugler
; Faculty of Natural Sciences, Ljubljana, Slovenia
M. Terčelj
; Faculty of Natural Sciences, Ljubljana, Slovenia
Sažetak
Genetic programming (GP) and CAE NN analysis have been applied for the prediction of bending capability of rolled ZnTiCu alloy sheet. Investigation revealed that an analysis with CAE NN is faster than GP but less accurate for lower amount of data. Both methods enable good assessment of separate influencing parameters in the complex system.
Ključne riječi
rolling; ZnTiCu alloy; bending; genetic programming; CAE neural networks
Hrčak ID:
26037
URI
Datum izdavanja:
1.10.2008.
Posjeta: 1.846 *