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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


Puni tekst: engleski pdf 653 Kb

str. 301-305

preuzimanja: 543

citiraj


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

https://hrcak.srce.hr/26037

Podaci na drugim jezicima: hrvatski

Posjeta: 888 *