Abstract
This paper analyses the effectiveness of determining gas concentrations by
using a prototype WO3 resistive gas sensor together with fluctuation
enhanced sensing. We have earlier demonstrated that this method can
determine the composition of a gas mixture by using only a single sensor.
In the present study, we apply Least-Squares Support-Vector-Machine-based
(LS-SVM-based) nonlinear regression to determine the gas concentration of
each constituent in a mixture. We confirmed that the accuracy of the
estimated gas concentration could be significantly improved by applying
temperature change and ultraviolet irradiation of the WO3 layer.
Fluctuation-enhanced sensing allowed us to predict the concentration of
both component gases.
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