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Evaluation of an optical phenolic biosensor signal employing artificial neural networks
- Source :
-
Sensors & Actuators B: Chemical . Sep2008, Vol. 134 Issue 2, p959-965. 7p. - Publication Year :
- 2008
-
Abstract
- Abstract: This paper presents artificial neural network (ANN)-based evaluation in signal processing of an optical phenolic biosensor. The biosensor was developed based on stacked immobilization of 3-methyl-2-benzothiazolinone hydrazone (MBTH) in hybrid Nafion/sol–gel silicate and tyrosinase in chitosan. The biosensor signal was simulated employing a feed-forward neural network with three layers and trained using back-propagation (BP) algorithm. Spectra generated from an optical phenolic biosensor at selected wavelengths were used as input data for ANN. The network architecture of 5 inputs neurons, 21 hidden neurons and 1 output neuron was found suitable for this application. The results show very good agreement between phenol concentration values obtained by using the developed biosensor and those predicted by ANN. [Copyright &y& Elsevier]
- Subjects :
- *DETECTORS
*ACTUATORS
*ARTIFICIAL neural networks
*ARTIFICIAL intelligence
Subjects
Details
- Language :
- English
- ISSN :
- 09254005
- Volume :
- 134
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Sensors & Actuators B: Chemical
- Publication Type :
- Academic Journal
- Accession number :
- 34435931
- Full Text :
- https://doi.org/10.1016/j.snb.2008.07.009