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.
|Title of host publication||International Conference on Oriental Thinking and Fuzzy Logic|
|Editors||Bing-Yuan Cao, Pei-Zhuang Wang, Zeng-Liang Liu, Yu-Bin Zhong|
|Place of Publication||Switzerland|
|ISBN (Print)||978-3-319-30873-9, 978-3-319-30874-6|
|Publication status||Published - 19 Jun 2016|
Bibliographical noteThe full text is not available on the repository.
- Interval-valued intuitionistic fuzzy sets
- Dynamic fuzzy sets
- Pattern classification
- Outsourced software project risk
Zhang, Z-H., Qu, G-H., Xiao, K-X., Hu, Y., Li, Z-J., Chen, X-X., ... Ma, C. (2016). Some Novel Dynamic Fuzzy Sets Models Applied to the Classification of Outsourced Software Project Risk. In B-Y. Cao, P-Z. Wang, Z-L. Liu, & Y-B. Zhong (Eds.), International Conference on Oriental Thinking and Fuzzy Logic (Vol. 443, pp. 273-286). Switzerland: Springer Verlag. https://doi.org/10.1007/978-3-319-30874-6_27