NEURAL NETWORKS AND ABDUCTIVE NETWORKS FOR CHEMICAL SENSOR SIGNALS - A CASE COMPARISON

Both artificial neural networks (ANNs) and the abductory induction mec hanism (AIM) have been proven to be suitable for the evaluation of sig nals from chemical sensors with strong interactions of gas components on the catalytically active surface. The algorithms allow the calculat ion of calibration curves for a multisensor. AIM yields a good mean ap proximation within a very short time; ANN covers a broader concentrati on range with an adequate approximation. The signal evaluation of a se t of two pellistors and another set of six MOSFETs is used for illustr ation.