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

Zhen-Hua Zhang, G.-H. Qu, K.-X. Xiao, Y. Hu, Z.-J. Li, X.-X. Chen, J.-H. Xu, C. Ma

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

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.
Original languageEnglish
Title of host publicationInternational Conference on Oriental Thinking and Fuzzy Logic
EditorsBing-Yuan Cao, Pei-Zhuang Wang, Zeng-Liang Liu, Yu-Bin Zhong
Place of PublicationSwitzerland
PublisherSpringer Verlag
Pages273-286
Volume443
ISBN (Print)978-3-319-30873-9, 978-3-319-30874-6
DOIs
Publication statusPublished - 19 Jun 2016

Bibliographical note

The full text is not available on the repository.

Keywords

  • Interval-valued intuitionistic fuzzy sets
  • Dynamic fuzzy sets
  • Pattern classification
  • Outsourced software project risk

Fingerprint Dive into the research topics of 'Some Novel Dynamic Fuzzy Sets Models Applied to the Classification of Outsourced Software Project Risk'. Together they form a unique fingerprint.

Cite this