An Artificial Neural Network Approach for the Prediction of Absorption Measurements of an Evanescent Field Fiber Sensor

This paper describes artificial neural network (ANN) based prediction of the response of a fiber optic sensor using evanescent field absorption (EFA). The sensing probe of the sensor is made up a bundle of five PCS fibers to maximize the interaction of evanescent field with the absorbing medium. Dif...

Descripción completa

Detalles Bibliográficos
Autor principal: Saracoglu, Ö. Galip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2008
Materias:
Full Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3663013/
https://www.ncbi.nlm.nih.gov/pubmed/27879782
_version_ 1782270919644807168
author Saracoglu, Ö. Galip
author_facet Saracoglu, Ö. Galip
author_sort Saracoglu, Ö. Galip
collection PubMed
description This paper describes artificial neural network (ANN) based prediction of the response of a fiber optic sensor using evanescent field absorption (EFA). The sensing probe of the sensor is made up a bundle of five PCS fibers to maximize the interaction of evanescent field with the absorbing medium. Different backpropagation algorithms are used to train the multilayer perceptron ANN. The Levenberg-Marquardt algorithm, as well as the other algorithms used in this work successfully predicts the sensor responses.
format Online
Article
Text
id pubmed-3663013
institution National Center for Biotechnology Information
language English
publishDate 2008
publisher Molecular Diversity Preservation International (MDPI)
record_format MEDLINE/PubMed
spelling pubmed-36630132013-05-30 An Artificial Neural Network Approach for the Prediction of Absorption Measurements of an Evanescent Field Fiber Sensor Saracoglu, Ö. Galip Sensors (Basel) Full Research Paper This paper describes artificial neural network (ANN) based prediction of the response of a fiber optic sensor using evanescent field absorption (EFA). The sensing probe of the sensor is made up a bundle of five PCS fibers to maximize the interaction of evanescent field with the absorbing medium. Different backpropagation algorithms are used to train the multilayer perceptron ANN. The Levenberg-Marquardt algorithm, as well as the other algorithms used in this work successfully predicts the sensor responses. Molecular Diversity Preservation International (MDPI) 2008-03-10 /pmc/articles/PMC3663013/ /pubmed/27879782 Text en © 2008 by MDPI Reproduction is permitted for noncommercial purposes.
spellingShingle Full Research Paper
Saracoglu, Ö. Galip
An Artificial Neural Network Approach for the Prediction of Absorption Measurements of an Evanescent Field Fiber Sensor
title An Artificial Neural Network Approach for the Prediction of Absorption Measurements of an Evanescent Field Fiber Sensor
title_full An Artificial Neural Network Approach for the Prediction of Absorption Measurements of an Evanescent Field Fiber Sensor
title_fullStr An Artificial Neural Network Approach for the Prediction of Absorption Measurements of an Evanescent Field Fiber Sensor
title_full_unstemmed An Artificial Neural Network Approach for the Prediction of Absorption Measurements of an Evanescent Field Fiber Sensor
title_short An Artificial Neural Network Approach for the Prediction of Absorption Measurements of an Evanescent Field Fiber Sensor
title_sort artificial neural network approach for the prediction of absorption measurements of an evanescent field fiber sensor
topic Full Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3663013/
https://www.ncbi.nlm.nih.gov/pubmed/27879782
work_keys_str_mv AT saracogluogalip anartificialneuralnetworkapproachforthepredictionofabsorptionmeasurementsofanevanescentfieldfibersensor
AT saracogluogalip artificialneuralnetworkapproachforthepredictionofabsorptionmeasurementsofanevanescentfieldfibersensor

Ejemplares similares