Related references
Note: Only part of the references are listed.Estimation of the minimum machining performance in the abrasive waterjet machining using integrated ANN-SA
Azlan Mohd Zain et al.
EXPERT SYSTEMS WITH APPLICATIONS (2011)
Application of GA to optimize cutting conditions for minimizing surface roughness in end milling machining process
Azlan Mohd Zain et al.
EXPERT SYSTEMS WITH APPLICATIONS (2010)
Comparison of Bayesian networks and artificial neural networks for quality detection in a machining process
M. Correa et al.
EXPERT SYSTEMS WITH APPLICATIONS (2009)
Adaptive network-based fuzzy inference system for prediction of surface roughness in end milling process using hybrid Taguchi-genetic learning algorithm
Wen-Hsien Ho et al.
EXPERT SYSTEMS WITH APPLICATIONS (2009)
Optimization of multi-pass face-milling via harmony search algorithm
O. Zarei et al.
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY (2009)
A novel hybrid immune algorithm for global optimization in design and manufacturing
Ali Riza Yildiz
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING (2009)
Application areas of AIS: The past, the present and the future
Emma Hart et al.
APPLIED SOFT COMPUTING (2008)
A fuzzy expert system for optimizing parameters and predicting performance measures in hard-milling process
Asif Iqbal et al.
EXPERT SYSTEMS WITH APPLICATIONS (2007)
Performance-based optimization of multi-pass face milling operations using Tribes
Godfrey C. Onwubolu
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE (2006)
An adaptive-network based fuzzy inference system for prediction of workpiece surface roughness in end milling
SP Lo
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY (2003)
Integrated genetic programming and genetic algorithm approach to predict surface roughness
M Brezocnik et al.
MATERIALS AND MANUFACTURING PROCESSES (2003)
A fuzzy-net-based multilevel in-process surface roughness recognition system in milling operations
JC Chen et al.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2001)