Integrated genetic programming and genetic algorithm approach to predict surface roughness
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- @Article{Brezocnik:2003:MMP,
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author = "Miran Brezocnik and Miha Kovacic",
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title = "Integrated genetic programming and genetic algorithm
approach to predict surface roughness",
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journal = "Materials and Manufacturing Processes",
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year = "2003",
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volume = "18",
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number = "3",
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pages = "475--491",
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month = may,
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keywords = "genetic algorithms, genetic programming, Manufacturing
systems, Surface roughness, Milling",
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DOI = "doi:10.1081/AMP-120022023",
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abstract = "we propose a new integrated genetic programming and
genetic algorithm approach to predict surface roughness
in end-milling. Four independent variables, spindle
speed, feed rate, depth of cut, and vibrations, were
measured. Those variables influence the dependent
variable (i.e., surface roughness). On the basis of
training data set, different models for surface
roughness were developed by genetic programming. The
floating-point constants of the best model were
additionally optimised by a genetic algorithm. Accuracy
of the model was proved on the testing data set. By
using the proposed approach, more accurate prediction
of surface roughness was reached than if only modelling
by genetic programming had been carried out. It was
also established that the surface roughness is most
influenced by the feed rate, whereas the vibrations
increase the prediction accuracy.",
- }
Genetic Programming entries for
Miran Brezocnik
Miha Kovacic
Citations