In this work we present the methods of creating the knowledge bases by using the theory of fuzzy systems as well as the probability and stochastic processes theory. We show that such knowledge-based systems can be applied in different diagnostic tasks. The structure of the reason-result fuzzy model is predefined by experts at the beginning of the task. The… (More)
In the article the possibility of applying one of the methods of data mining – fuzzy association rules to model fuzzy systems is presented. The algorithm of automatic extracting knowledge base is a modification of the Apriori algorithm. The obtained rules of the model contain weights, that are calculated on the basis of measures of fuzzy association rules… (More)
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… (More)
This paper is focused on the extending Takagi-Sugeno-Kang (TSK) types fuzzy models. The propositions of the models with a fuzzy set-valued function in the consequence part as well as the models with the fuzzy time series in the consequence part are presented. Also chosen theoretical aspects of the creating knowledge bases and the fuzzy reasoning procedure… (More)
The paper deals with the ideas of a linguistic knowledge representation and a probability of fuzzy events. Linguistic fuzzy model with weights of rules is considered as a model of a probabilistic MISO system. The probabilities of linguistic values of antecedent and consequent variables are proposed as rule weights. The linguistic inference procedure and an… (More)
This paper presents a proposition of the knowledge representation and the inference procedure including two types of uncertainty: probabilistic and fuzzy. Added weights to the fuzzy rule-based model state probabilities of fuzzy events in antecedents and consequents. The exemplary calculations are presented.
The paper deals with an idea of a linguistic knowledge representation and a linguistic inference. Relational linguistic fuzzy model with weights of rules is utilising. The probability of linguistic values of antecedent and consequent variables, calculated according to Zadeh's definition, is proposed to formulate a linguistic fuzzy model of a stochastic… (More)