Fuzzy knowledge-based approach to diagnosis tasks in stochastic environment

This work deals with the creating probabilistic-fuzzy knowledge-based systems by using the theory of fuzzy systems as well as the probability and stochastic processes theory. We show that such systems can be applied in different diagnostic tasks. The structure of the reason-result fuzzy model has a form of weighted rules. Weights represent empirical probabilities of fuzzy statements in antecedents and consequent parts of rules. The calculated probabilities of fuzzy events are included into inference/forecast procedures.