Modelling Uncertain Data

A₁ algorithm application approach approximation assumed B₁ Bandemer Bayes Bayesian inference Bayesian Statistics C₁ calculation characterizing function Chemnitz coefficients computation concept considered constraints corresponding crisp decision defined denotes density derivative domain eigenvalues enclosing sets enclosure estimates evaluation example expert systems extension principle Figure finite element finite element method fuzzy data analysis fuzzy numbers fuzzy random variable fuzzy set theory given grey-tone pictures Hessian matrix I(IR imprecise inference interpretation interval mathematics IRē Kruse Linear Programming linguistic variables M₁ matrix measure membership function methods non-precise data nonlinear observations obtained operations optimal control parameters Pilz possible posterior prior distribution probability problem Prof random variable resp respect robustness Rommelfanger rule SBUs Sets and Systems space specified stochastic subset t-norm Theorem truth value uncertain uncertainty V-DATA vague data vector Zadeh Zi+1 θη μη