RT Journal Article
SR Electronic
A1 Trzepieciński, Tomasz
A1 Lemu Gelgele, Hirpa
T1 Application of Genetic Algorithm for Optimization of Neural Networks for Selected Tribological Test
JF Acta Mechanica Slovaca
YR 2012
VO 16
IS 2
SP 54
OP 60
DO 10.21496/ams.2012.019
UL https://www.actamechanica.sk/artkey/ams-201202-0008.php
AB In this work was presented the method of determination of the friction coefficient by using multilayer artificial neural networks on the basis of experimental database obtained from the strip drawing test. Using genetic algorithm the optimization of number of input variables of artificial neural networks has been done. As an input parameters for training artificial neural networks following parameters has been used: surface parameters of the sheet and dies, sheet material parameters and clamping force. Some results have pointed out that genetic algorithm has been successfully appled to optimization of training set.