Modelling Uncertain Data

a₁ algorithm application approach approximation assumed B₁ Bandemer Bayes Bayesian inference Bayesian Statistics Berlin C₁ calculation characterizing function Chemnitz coefficients computation concept considered constraints context model 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 relations fuzzy set theory given grey-tone pictures H-DATA Hessian matrix imprecise inference interpretation interval mathematics Kruse Linear Programming linguistic variables MARKETGROWTH matrix measure membership function methods non-precise data nonlinear objects observations obtained operations optimal control parameters Pilz possible posterior prior distribution probability problem Prof random variable RELATIVE_SHARE resp respect robustness Rommelfanger rule Sets and Systems space specified stochastic subset t-norm Theorem truth value uncertain uncertainty vague data vector Zadeh Zi+1