Journal article
Artificial neural networks for the automated detection of trichloroethylene by passive Fourier transform infrared spectrometry
Analytical chemistry (Washington), Vol.72(7), pp.1680-1689
2000
DOI: 10.1021/ac991075s
PMID: 10763269
Abstract
Artificial neural networks are applied to the automated classification of trichloroethylene (TCE) signatures from passive Fourier transform infrared remote sensing interferogram data. Through the use of three data collection methods, a combination of laboratory and field data is acquired that allows the methodology to be evaluated under a variety of infrared background conditions and in the presence of potentially interfering compounds such as sulfur hexafluoride, methyl ethyl ketone, acetone, carbon tetrachloride, and ammonia. To maximize the computational efficiency of the network optimization, experimental design techniques are employed to develop a training protocol for the network that takes into account the relationships among five variables that are related either to the network architecture or to the training process. This protocol is implemented for the case of a back- propagation neural network (BNN) and is used to develop an optimized network for the detection of TCE. The classification performance of the network is assessed by comparing both TCE detection capabilities and false detection rates to similar classification results obtained with the technique of piecewise linear discriminant analysis (PLDA). When applied to prediction data withheld from the optimization of both the BNN and PLDA algorithms, the BNN method is observed to outperform PLDA overall, with TCE detection rates in excess of 99% and false detection rates less than 0.5%.
Details
- Title: Subtitle
- Artificial neural networks for the automated detection of trichloroethylene by passive Fourier transform infrared spectrometry
- Creators
- Cheryl L Hammer - Center for Intelligent Chemical Instrumentation, Department of Chemistry and Biochemistry, Clippinger Laboratories, Ohio University, Athens, Ohio 45701-2979, United StatesGary W Small - Center for Intelligent Chemical Instrumentation, Department of Chemistry and Biochemistry, Clippinger Laboratories, Ohio University, Athens, Ohio 45701-2979, United StatesRoger J Combs - U.S. Army, SBCCOM, Edgewood Chemical Biological Center, Aberdeen Proving Ground, Maryland 21010-5424, United StatesRobert B Knapp - U.S. Army, SBCCOM, Edgewood Chemical Biological Center, Aberdeen Proving Ground, Maryland 21010-5424, United StatesRobert T Kroutil - U.S. Army, SBCCOM, Edgewood Chemical Biological Center, Aberdeen Proving Ground, Maryland 21010-5424, United States
- Resource Type
- Journal article
- Publication Details
- Analytical chemistry (Washington), Vol.72(7), pp.1680-1689
- Publisher
- American Chemical Society
- DOI
- 10.1021/ac991075s
- PMID
- 10763269
- ISSN
- 0003-2700
- eISSN
- 1520-6882
- Language
- English
- Date published
- 2000
- Academic Unit
- Chemistry
- Record Identifier
- 9984216698402771
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