The fuzzy development and adaptation of statistical and numerical methods to applications to technical and medical models with imprecise data
Elisabeth Rakus-Andersson · 2002
All the solutions to the problems sketched below will be created on the basis of Fuzzy Set Theory. Fuzzy Set Theory is applied instead of the classical set theory when data involved in the problem to solve is imprecise, verbally described or cannot be measured exactly. The models, which are the contents of the project should contain some proposed solutions to such problems as: 1) the approximation of the mean value and the standard deviation for some imprecise data, 2) a probability distribution filled with fuzzy probability sets (Yager’s probabilities) that replace the probability values from the normal distribution, 3) the application of the last distribution to statistical tests with imprecise data, 4) the development of Factor Analysis for qualitative variables and factors provided that the data is collected by means of a questionnaire, 5) the interpolation of a set of points with imprecise coordinates by a fuzzy function.