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Analysis of systems under probabilistic and fuzzy uncertainty using multi-valued logic

This paper introduces a special class of functions characterised by two interrelated mappings—logical and probabilistic. This formal theory is implemented by means of input–output sets of data from real multi-factor, multi-stage, non-stationary processes 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 these functions.