Title

Determination Of Gas Mixture Components Using Fluctuation Enhanced Sensing And The LS-SVM Regression Algorithm

Journal title

Metrology and Measurement Systems

Yearbook

2015

Volume

vol. 22

Issue

No 3

Authors

Lentka, Łukasz ; Smulko, Janusz M. ; Ionescu, Radu ; Granqvist, Claes G. ; Kish, Laszlo B.

Keywords

LS-SVM algorithm ; resistance gas sensor ; fluctuation enhanced sensing ; gas detection

Divisions of PAS

Nauki Techniczne

Coverage

341-350

Publisher

Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation

Date

2015[2015.01.01 AD - 2015.12.31 AD]

Type

Artykuły / Articles

Identifier

DOI: 10.1515/mms-2015-0039 ; ISSN 2080-9050, e-ISSN 2300-1941

Source

Metrology and Measurement Systems; 2015; vol. 22; No 3; 341-350

References

Nguyen (2010), la Optimal feature selection for support vector machines, Pattern Recognition, 43, 584, doi.org/10.1016/j.patcog.2009.09.003 ; Kalinowski (2013), Efficiency of linear and nonlinear classifiers for gas identification from electrocatalytic gas sensor, Metrol Meas Syst, 20, 501, doi.org/10.2478/mms-2013-0043 ; Kwiatkowski (2014), Detection of denatonium benzoate Bitrex remnants in noncommercial alcoholic beverages by raman spectroscopy of, Journal Forensic Sciences, 59. ; Kotarski (2009), Noise measurement set - ups for fluctuations - enhanced gas sensing, Metrol Meas Syst, 16, 457. ; Kuhn (1951), Nonlinear programming of the nd Berkeley Symposium Berkeley University of California Press, Proc, 1951. ; Kumar (2012), A simple electronic tongue and, Sensors Actuators Chemical, 171. ; Korotcenkov (2013), Engineering approaches for the improvement of conductometric gas sensor parameters Part Improvement of sensor sensitivity and selectivity ( short survey ) and, Sensors Actuators Chemical, 1. ; Aydin (2011), A multi - objective artificial immune algorithm for parameter optimization in support vector machine, Applied Soft Computing, 11, 120, doi.org/10.1016/j.asoc.2009.11.003 ; Zakrzewska (2001), Mixed oxides as gas sensors Solid, Thin Films, 391. ; Barman (2012), Investigation of noise - induced instabilities in quantitative biological spectroscopy and its implications for noninvasive glucose monitoring, Analytical Chemistry, 19, 84. ; Pardo (2005), Classification of electronic nose data with support vector machines and, Sensors Actuators Chemical, 107. ; Adankon (2009), Model selection for the LS - SVM Application to handwriting recognition, Pattern Recognition, 42, 3264, doi.org/10.1016/j.patcog.2008.10.023 ; Granqvist (2008), Electrochromic foil - based devices : Optical transmittance and modulation range , effect of ultraviolet irradiation , and quality assessment by fcurrent noise Solid, Thin Films, 17, 1. ; Chauchard (2004), Application of LS - SVM to non - linear phenomena in NIR spectroscopy : development of a robust and portable sensor for acidity prediction in grapes and Intelligent Laboratory, Chemometrics Systems, 71. ; Osowski (2014), Differential electronic nose in on - line dynamic measurements, Metrol Meas Syst, 21, 649, doi.org/10.2478/mms-2014-0053 ; Ayhan (2013), Fluctuation enhanced sensing ( FES ) with a nanostructured , semiconducting metal oxide film for gas detection and classification and, Sensors Actuators Chemical, 188. ; Kish (2000), Extracting information from noise spectra of chemical sensors : single sensor electronic noses and tongues and, Sensors Actuators Chemical, 71. ; Vapnik (2000), The nature of statistical learning theory New York Business Media, Science. ; Kwiatkowski (2010), Algorithms of chemicals detection using raman spectra, Metrol Meas Syst, 17, 549, doi.org/10.2478/v10178-010-0045-1 ; Kaur (2012), Enhancing electronic nose performance : A novel feature selection approach using dynamic social impact theory and moving window time slicing for classification of Kangra orthodox black tea ( Camellia Sinensis Sensors and, Actuators Chemical, 166. ; Mroczka (2013), The cognitive process in metrology, Measurement, 46, 2896, doi.org/10.1016/j.measurement.2013.04.040