Comparative study of neural networks and least mean square algorithm applied to the optimization of cosmetic formulations.

Abstract:

:In this work, a comparative study between two methods to acquire relevant information about a cosmetic formulation has been carried out. A Design of Experiments (DOE) has been applied in two stages to a capillary cosmetic cream: first, a Plackett-Burman (PB) design has been used to reduce the number of variables to be studied; second, a complete factorial design has been implemented. With the experimental data collected from the DOE, a Least Mean Square (LMS) algorithm and Artificial Neural Networks (ANN) have been utilized to obtain an equation (or model) that could explain cream viscosity. Calculations have shown that ANN are the best prediction method to fit a model to experimental data, within the interval of concentrations defined by the whole set of experiments.

journal_name

Int J Cosmet Sci

authors

Balfagón AC,Serrano-Hernanz A,Teixido J,Tejedor-Estrada R

doi

10.1111/j.1468-2494.2009.00565.x

subject

Has Abstract

pub_date

2010-10-01 00:00:00

pages

376-86

issue

5

eissn

0142-5463

issn

1468-2494

pii

ICS565

journal_volume

32

pub_type

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