z-logo
open-access-imgOpen Access
Prediction of S urface R oughness in End Milling Of P20 Mould Steel Using Artificial Neural Networks
Author(s) -
K. Vijaya Kumar Reddy,
N. Jaya Krishna,
Jitender Kumar
Publication year - 2012
Publication title -
journal of engineering science and technology review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.19
H-Index - 28
eISSN - 1791-9320
pISSN - 1791-2377
DOI - 10.25103/jestr.051.02
Subject(s) - artificial neural network , taguchi methods , multilayer perceptron , surface roughness , orthogonal array , end milling , engineering , design of experiments , nonlinear system , mechanical engineering , materials science , computer science , artificial intelligence , mathematics , machine learning , statistics , composite material , machining , physics , quantum mechanics

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom