NONLINEAR FUZZY LINGUISTICS FOR THE DETERMINATION OF NITROGEN MONOXIDE, NITROGEN DIOXIDE, AND SULFUR DIOXIDE BY MOLECULAR ABSORPTION SPECTROSCOPY

The nonlinearity and high dimensionality of spectra data affect the precision and the complexity of molecular absorption spectroscopy models. This article proposes a nonlinear fuzzy linguistic method for spectral quantitative analysis. A nonlinear fuzzy linguistic rule is presented. In the rule antecedent, a set operation was used to express the input variables by the fuzzy linguistic terms. A flexible polynomial equation of the input variables was the rule consequent. The fuzzy linguistic terms, the membership functions, and the nonlinear linguistic rules were initialized automatically by Gaussian kernel fuzzy clustering analysis, and the related parameters of nonlinear fuzzy linguistic rules were tuned by the iterative optimization for minimizing the root-mean square error. The principal components of the absorption measurements were extracted as input variables to reduce the complexity of the model. Experimental measurements employed a spectral dataset of flue gas for quantitative determination of the components that included sulfur dioxide, nitric oxide, and nitrogen dioxide. The experimental results verify the effectiveness of the theoretical approach.