Analysis of systems under probabilistic and fuzzy uncertainty using multivalued logic

This paper introduces a special class of functions characterised by two reciprocally connected mappings - logical and probabilistic. The adequacy of this formal instrument is established through input-output sets of data from real multifactor multistage plants operating under stochastic and fuzzy uncertainty of the environment. It is shown how incorrect data can be successfully processed for prediction and control purposes by applying interpolation, composition and extrapolation procedures to the above class of functions.