Classification of aged wine distillates using fuzzy and neural network systems Original Research Article

The classification of aged wine distillates is a non-linear, multi-criteria decision-making problem characterized by overwhelming complexity, non-linearity and lack of objective information regarding the desired final product qualitative characteristics. The most efficient solution for the evaluation of aged wine distillates estimations with emphasis on the properties of the aroma and the taste, when an appropriate mathematical model cannot be found, is to develop adequate and reliable expert systems based on fuzzy logic and neural networks. A fuzzy classifier and a neural network are proposed for the classification of wine distillates for each of two distinct features of the products namely the aroma and the taste. The fuzzy classifier is based on the fuzzy k-nn algorithm while the neural system is a feedforward sigmoidal multilayer network which is trained using the back-propagation method. The results show that both fuzzy and neural classification systems performed remarkably well in the evaluation of the aroma and the taste of the products.