Title of article
Prediction of Burnishing Surface Integrity using Radial Basis Function
Author/Authors
EL-Tayeb, N.S.M. university of malaya - Faculty of Engineering - Mechanical Engineering Department, Malaysia , Purushothaman, S. Multimedia University - Faculty of Engineering and Technology, Malaysia
From page
391
To page
399
Abstract
In this work, prediction of burnishing surface quality such as roughness (Ra) and Vickers hardness (HV) were achieved by using supervised radial basis function (RBF). The process state variables used were burnishing speed, feed, and depth. RBF has achieved a minimum of 90.62 % of prediction and proved to be convenient in terms of least computational complexity and dealing with nonlinear data such as obtained in this work.
Keywords
Artificial Neural Network , Radial Basis Function , Burnishing process
Journal title
International Journal of Mechanical and Materials Engineering
Journal title
International Journal of Mechanical and Materials Engineering
Record number
2565943
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