ANN in modeling the machining process
The former, which is defined as modeling of machining processes, is essential to provide the basic mathematical models for formulation of the certain process objective functions. With conventional approaches such as Statistical Regressio...
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| Main Authors: | , , |
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| Format: | Book Section |
| Published: |
Penerbit UTM
2008
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| Subjects: | |
| Online Access: | http://eprints.utm.my/16804/ |
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| Summary: | The former, which is defined as modeling of
machining processes, is essential to provide the basic
mathematical models for formulation of the certain process
objective functions. With conventional approaches such as
Statistical Regression technique, explicit models are developed
that required complex physical understanding of the modeling
process. With non conventional approaches or Artificial
Intelligence techniques such as Artificial Neural Network,
Fuzzy Logic and Genetic Algorithm based modeling, implicit
model are created within the weight matrices of the net, rules
and genes that is easier to be implemented. With the focus on
surface roughness performance measure, this paper outlines
and discusses the concept, application, abilities and limitations
of Artificial Neural Network in the machining process
modeling. Subsequently the future trend of Artificial Neural
Network in modeling machining process is reported. |
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