Some Novel Dynamic Fuzzy Sets Models Applied to the Classification of Outsourced Software Project Risk

Abstract

Some novel dynamic fuzzy sets (DFS) models, which are the generalization of fuzzy sets (FS) and the dynamization of interval-valued intuitionistic fuzzy sets (IVIFS), are presented in this paper. First, we propose some weighted DFS models from IVIFS. Second, we introduce the distance formula of DFS. Finally, we apply these DFS models and the distance measures to pattern classification of outsourced software project risk to demonstrate the advantages of these DFS models, and the experimental results show that these DFS models are more effective than the conventional clustering algorithms and IVIFS model in pattern classification.