The sorption of methanol and ethanol vapors by a microporous glassy polycarbonate is studied. The increase of the refractive index of the polymer during analyte sorption is measured by surface plasmon resonance. Both analytes are sorbed into the micropores of the polymer showing different diffusion kinetics. The sensor response during analyte exposure is subdivided into different time channels. By evaluating this additional data dimension by neural networks, a simultaneous multicomponent analysis of binary mixtures of ethanol and methanol vapors is possible using the sensor response of only one single sensor. A feature extraction results in an interpretable model and an improved prediction with errors of 2.0% for methanol and 2.4% for ethanol.