|||Uwe Wagner, Statistical Based Fuzzy Sets, in proc. Nafips, 2002.
We present a methodology for semantic fuzzy sets. We construct
alpha-cuts on the basis of observed data. Therefore we do no longer
need exclusively triangles, trapeziums or Gauss curves as elementary
form for fuzzy sets. In addition to that, we are able to integrate
expert opinions, modelled as fuzzy sets. The methodology combines
statistical interval estimation and distribution tests with fuzzy
logic. It is applicable to random processes with an insufficient
number of sample points. If the sample size increases, the result
converges toward the statistical estimators. We applied the method to
estimate the discharge of a river.