20.500.12556/DKUM-27532 Prediction of surface roughness with genetic programming In this paper we propose genetic programming to predict surface roughness in end-milling. Two independent data sets were obtained on the basis of measurement: training data set and testing data set. Spindle speed, feed rate,depth of cut, and vibrations are used as independent input variables (parameters), while surface roughness as dependent output variable. On the basis of training data set, different models for surface roughness were developed by genetic programming. Accuracy of the best model was proved with the testing data. It was established that the surface roughness is most influenced by the feed rate, whereas the vibrations increase the prediction accuracy. end milling surface roughness prediction of surface roughness genetic programming čelno frezanje površinska hrapavost napoved hrapavosti genetsko programiranje true false false Angleški jezik Angleški jezik Neznano 2012-06-01 11:36:12 2012-06-01 11:36:12 2022-04-15 03:45:08 2019-07-10 12:18:45 2004 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 621.914:004.89 9026582 0924-0136 URN:SI:UM:DK:CX2LMQOO http://dx.doi.org/10.1016/j.jmatprotec.2004.09.004 1 https://dk.um.si/Dokument.php?lang=slv&id=36833 Fakulteta za strojništvo 0 0 0