Reducing overfitting in manufacturing process modeling using a backward elimination based genetic programming

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Reducing overfitting in manufacturing process modeling using a backward elimination based genetic programming

Genetic programming (GP) has demonstrated as an effective approach in polynomial modeling of manufacturing processes. However, polynomial models with redundant terms generated by GP may depict overfitting, while the developed models have good accuracy on trained data sets but relatively poor accurac...

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Bibliographic Details
Main Authors:	Chan, Kit Yan, Kwong, C., Dillon, Tharam S., Tsim, Y.
Format:	Journal Article
Published:	Elsevier 2010
Subjects:	Genetic programming Polynomial modeling Overfitting Process modeling
Online Access:	http://hdl.handle.net/20.500.11937/10336

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