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Sensors 2008, 8(3), 1585-1594; doi:10.3390/s8031585

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

Erciyes University, Department of Electrical and Electronic Engineering, 38039, Kayseri, Turkey
Received: 2 November 2007 / Accepted: 29 February 2008 / Published: 10 March 2008
(This article belongs to the Special Issue Intelligent Sensors)
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Abstract

This paper describes artificial neural network (ANN) based prediction of theresponse of a fiber optic sensor using evanescent field absorption (EFA). The sensingprobe of the sensor is made up a bundle of five PCS fibers to maximize the interaction ofevanescent field with the absorbing medium. Different backpropagation algorithms areused to train the multilayer perceptron ANN. The Levenberg-Marquardt algorithm, aswell as the other algorithms used in this work successfully predicts the sensor responses.
Keywords: Fiber optic sensor; evanescent field; absorption; artificial neural networks Fiber optic sensor; evanescent field; absorption; artificial neural networks
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Saracoglu, Ö.G. An Artificial Neural Network Approach for the Prediction of Absorption Measurements of an Evanescent Field Fiber Sensor. Sensors 2008, 8, 1585-1594.

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