Uncertain Fuzzy Clustering: Insights and Recommendations
- Title
- Uncertain Fuzzy Clustering: Insights and Recommendations
- Author
- 이정훈
- Issue Date
- 2007-02
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Citation
- IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, v. 2, No. 1, Page. 44-56
- Abstract
- Interval type-2 fuzzy sets were used to model the uncertainty that is associated with the various parameters in objective function-based clustering. The purpose was to represent and manage the uncertainty in the cluster memberships by incorporating interval type-2 fuzzy sets. As a result, interval type-2 clustering methods were obtained by modifying the prototype-updating and hard-partitioning procedures in the type-1 fuzzy objective function-based clustering. As a consequence, the management of uncertainty by an interval type-2 fuzzy approach aids cluster prototypes to converge to a more desirable location than a type-1 fuzzy approach. Several examples illustrated the effectiveness of interval type-2 fuzzy approach methods. Furthermore, the uncertainty associated with the parameters for other existing clustering algorithms can be considered in the development of several other interval type-2 clustering algorithms. They are currently under investigation.
- URI
- https://ieeexplore.ieee.org/abstract/document/4195041https://repository.hanyang.ac.kr/handle/20.500.11754/106285
- ISSN
- 1556-603X; 1556-6048
- DOI
- 10.1109/MCI.2007.357193
- Appears in Collections:
- COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > ELECTRICAL ENGINEERING(전자공학부) > Articles
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML