A variance-based, BIC-penalized variable selection method identifies influential interferents in sensor calibration and improves pollutant prediction in simulated and outdoor carbon nanotube sensor settings.
Joint outdoor ozone and carbon monoxide prediction with a carbon nanotube sensor array calibrated using a bayesian framework
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Variance-based variable selection in sensor calibration with strong interferents -- application to air pollution monitoring with a carbon nanotube sensor array
A variance-based, BIC-penalized variable selection method identifies influential interferents in sensor calibration and improves pollutant prediction in simulated and outdoor carbon nanotube sensor settings.