Hydrogen, Fuel Cell & Energy Storage

Hydrogen, Fuel Cell & Energy Storage

Modeling of measurement error in refractive index determination of fuel cell using neural network and genetic algorithm

Document Type : Research Paper

Authors
Saeed Olyaee
Reza Ebrahimpour
Somayeh Esfandeh
Shahid Rajaee Teacher Training University
10.22104/ijhfc.2014.30
Abstract
Abstract: In this paper, a method for determination of refractive index in membrane of fuel cell on basis of three-longitudinal-mode laser heterodyne interferometer is presented. The optical path difference between the target and reference paths is fixed and phase shift is then calculated in terms of refractive index shift. The measurement accuracy of this system is limited by nonlinearity error. In this study, nonlinearity error is modeled by multi-layer perceptrons (MLPs) and stacked generalization method (Stacking), using two learning methods; back propagation (BP) and genetic algorithm. Training neural networks with genetic algorithm, improves modeling of nonlinearity error in this system. In the proposed technique, a real code version of genetic algorithm is used. Parameters and genetic operators are set and designed accurately. The results indicate that the nonlinearity error can be effectively modeled by training the stacking with the genetic algorithm which has minimum mean square error (MSE).
Keywords: Fuel cell, Genetic algorithm, Heterodyne interferometer, Multi-layer perceptrons, Nonlinearity error, Refractive index, Stacked Generalization.
Keywords
fuel cell
Genetic algorithm
Heterodyne interferometer
Subjects
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Hydrogen, Fuel Cell & Energy Storage
Volume 1, Issue 2 - Serial Number 2
Spring 2014
Pages 95-104