Identification of Lamda-fuzzy Measure by Modified Genetic Algorithms

摘要

Fuzzy measure is subjective scale for the degrees of fuzziness and suitable for analyzing human subjective evaluation processes. It is not easy to provide consistent fuzzy measure values with fuzzy measure properties since they have to be subjective determined. Thus it induces an identification problem that determines measure values with fuzzy measure properties from human-provided. The λ-fuzzy measure is a typical fuzzy measure widely used. Although several studies have been made on λ-fuzzy measure identification, the corresponding computation process is rather complicated and the result is not ideal. In this paper, we introduce a method for identification of λ-fuzzy measures from data set. It is implemented by using modified genetic algorithm and example data is tested, the result shows its applicability.