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Disambiguation of "Nieto, P. J. García"

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The use of design of experiments to improve a neural network model in order to predict the thickness of the chromium layer in a hard chromium plating process.

, , , and . Math. Comput. Model., 52 (7-8): 1169-1176 (2010)

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Luisa García García

Julio Abraham García García

Guillermo García

Huber Nieto-Chaupis

Isidro Nieto

 

Other publications of authors with the same name

Mathematical study of the selective removal of different classes of atmospheric aerosols by coagulation, condensation, and gravitational settling, and the health impact., , , and . Int. J. Comput. Math., 85 (3&4): 447-460 (2008)Non-linear thermal analysis of the efficiency of light concrete multi-holed bricks with large recesses by FEM., , , and . Appl. Math. Comput., 218 (20): 10040-10049 (2012)Non-linear analysis of a reinforced concrete sheet cover (umbrella) of 40m diameter by the finite element method., , , , and . Appl. Math. Comput., 184 (1): 37-51 (2007)Steady state numerical simulation of the particle collection efficiency of a new urban sustainable gravity settler using design of experiments by FVM., , , and . Appl. Math. Comput., 217 (21): 8166-8178 (2011)Non-linear numerical analysis of a double-threaded titanium alloy dental implant by FEM., , , and . Appl. Math. Comput., 206 (2): 952-967 (2008)Modeling pressure drop produced by different filtering media in microirrigation sand filters using the hybrid ABC-MARS-based approach, MLP neural network and M5 model tree., , , , , and . Comput. Electron. Agric., (2017)Non-linear analysis of the consolidation of an elastic saturated soil with incompressible fluid and variable permeability by FEM., , , and . Appl. Math. Comput., 216 (2): 458-476 (2010)The use of design of experiments to improve a neural network model in order to predict the thickness of the chromium layer in a hard chromium plating process., , , and . Math. Comput. Model., 52 (7-8): 1169-1176 (2010)Non-linear analysis and warping of tubular pipe conveyors by the finite element method., , , , , and . Math. Comput. Model., 46 (1-2): 95-108 (2007)Forecast of the higher heating value in biomass torrefaction by means of machine learning techniques., , , , and . J. Comput. Appl. Math., (2019)