Abstract
The paper deals with an application of probabilistic sets in system theory, especially in identification problems in systems described by means of max-min fuzzy relational equations. The identification procedures discussed are based on some ideas of iterative clustering techniques (ISODATA and FUZZY C-MEANS) which lead to a concrete method of determination of probabilistic sets. A vagueness function associated with the fuzzy relation of the system forms a validity indicator of the identification algorithm. Numerical examples containing fuzzy and nonfuzzy data form an illustration of the methods provided.