Artificial Neural Network and Response Surface Methodology Modeling in Ionic Conductivity Predictions of Phthaloylchitosan-Based Gel Polymer Electrolyte.
Polymers (Basel)
; 8(2)2016 Jan 29.
Article
em En
| MEDLINE
| ID: mdl-30979129
ABSTRACT
A gel polymer electrolyte system based on phthaloylchitosan was prepared. The effects of process variables, such as lithium iodide, caesium iodide, and 1-butyl-3-methylimidazolium iodide were investigated using a distance-based ternary mixture experimental design. A comparative approach was made between response surface methodology (RSM) and artificial neural network (ANN) to predict the ionic conductivity. The predictive capabilities of the two methodologies were compared in terms of coefficient of determination R² based on the validation data set. It was shown that the developed ANN model had better predictive outcome as compared to the RSM model.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Polymers (Basel)
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
Malásia
País de publicação:
CH
/
SUIZA
/
SUÍÇA
/
SWITZERLAND