Abstract
With the rapid changes in the global marketplace, using available data to build a management model has become increasingly difficult because the necessary information is often insufficient and incomplete. In the real world, the occurrence of some rare events may have a widespread socioeconomic impact and may cause significant losses. The data type of these rare events is mostly discrete. Thus, this study proposes a systematic way of filling information gaps and recognizing their underlying patterns accurately.An intuitive method based on the concept of analysis is presented to generate virtual samples. Moreover, by applying the extension principle in the fuzzy set theory, the degree of belonging of a generated datum to the discrete sample set can be described. The proposed method is therefore called fuzzy data construction method. Numerical example is provided to illustrate the procedure.