Development of decision-making technique for assessing knowledge considering probabilistic updating algorithm of membership functions

Abstract

This paper considers the decision-making technique through the analysis of testing knowledge results under incompleteness of initial information. This technique is notable for determination of testing system parameters as linguistic variables and the probabilistic updating algorithm of membership functions, as well as the decision-making model on the base of the classification of fuzzy situations and the composition model of fuzzy inference rules, that contribute to the well-known statistical models of testing results estimates.