Классификация многомерных данных с использованием кластерного генетического алгоритма и нечеткой логики

The paper describes the approach to the accuracy increasing of classification rules, obtained by genetic clustering algorithm. Proposed approach uses the theory of fuzzy sets, allowing to lower the uncertainly during classification process. The approach permits to take decisions, considering the whole set of rules, activated by the experimental observation.