Modelling Uncertain Data

Real data as used in application are always subject to uncertainty as variability, impreciseness and vagueness. By neglecting of this uncertainty the conclusion drawn from these data can give a euphoric impression of preciseness and can even become useless for application. Hence several approaches were developed allowing for a modelling of uncertainty: sensitivity analysis, interval mathematics, stochastics, fuzzy data analysis and statistics with fuzze data. This collection contains survey contributions on all these fields and, additionally, on optimization with fuzzy data. Each survey is followed by about three special papers, complementing it by presenting special aspects or application situations. All the contributions were invited lectures for a discussion workshop, where the approaches, their conditions, advantages and special application fields are presented and compared. Hence the colleciton contains all these concepts for dealing with real-world data in mathematical problems.