چکیده مقاله
Surface roughness is one of the essential quality characteristics that must be precisely controlled Artificial neural network modeling is a method of surface roughness prediction In this study, two different networks are used for surface roughness prediction in turning processes Experimental data for turning of 6061 T6511 Aluminum alloy, obtained from literature were employed to train the ANN models These ANNs were trained by Levenberg – Marquardt and Bayesian regularization algorithms Results show that the Bayesian regularization network has better prediction accuracy in comparison with Levenberg Marquardt algorithm A comparison of ANN model with regression model was also carried out
کلیدواژهها
نویسندگان
R Madoliat
Assistant professor, Iran University of Science and Technology
F jafarvand
MSc Student of Manufacturing engineering
R Raei
MSc Student of Manufacturing engineering
شیوه ارجاع
Madoliat, R and jafarvand, F and Raei, R,1384,Performance of Bayesian Regularization Neural- Network in Prediction of Surface Roughness,01st Tehran International Congress on Manufacturing Engineering (TICME2005),Tehran
ارائهشده در
مجموعه مقالات اولین کنفرانس بین المللی و هفتمین کنفرانس ملی مهندسی ساخت و تولید1 فروردین 1384 · تهران