GA-PARSIMONY: A GA-SVR approach with feature selection and parameter optimization to obtain parsimonious solutions for predicting temperature settings in a continuous annealing furnace

Autor: Pernía Espinoza, Alpha VerónicaAntoñanzas Torres, Fernando Jesús; FERNANDEZ CENICEROS, JULIO; Martínez de Pisón Ascacíbar, Francisco Javier; SANZ GARCÍA, ANDRÉS; 

Tipo de documento: Artículo de revista

Revista: Applied Soft Computing Journal. ISSN: 1568-4946. Año: 2015. Volumen: 35. Páginas: 13-28.

Texto completo open access 

JCR (datos correspondientes al año 2014):
Science  Área: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE  Quartil: Q1  Lugar área: 17/123  F. impacto: 2,810 
Science  Área: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS  Quartil: Q1  Lugar área: 17/123  F. impacto: 2,810 

SCIMAGO (datos correspondientes al año 2014):
2,22  SNIP: 2,729 



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