| Abstract: | An adaptive network–based fuzzy inference system, ANFIS, has been used for predicting dye concentrations using spectroscopic absorbance data in the visible region. The samples were two–component red/yellow dye solutions with a concentration range of 0–900 mg/l for the one component (red) while the concentration of the other component (yellow) was kept constant. The modelled system had two inputs (wavelength and absorbance) with the concentration values as output. Generalised bell–shaped membership functions were used for the inputs. The inference system used was a first–order Sugeno fuzzy model. The ANFIS models gave concentration prediction results with approximately the same standard error of prediction as artificial neural network (ANN) models. However, the ANFIS model building runs faster than in the case of ANN. |
