Output details
11 - Computer Science and Informatics
University of Manchester
Article title
An Output-Constrained Clustering Approach for the Identification of Fuzzy Systems and Fuzzy Granular Systems
Type
D - Journal article
Title of journal
IEEE Transactions on Fuzzy Systems
Article number
-
Volume number
19
Issue number
6
First page of article
1127
ISSN of journal
1063-6706
Year of publication
2011
URL
-
Number of additional authors
2
Additional information
<12> Cluster identification is a key issue in clustering, a major technique in unsupervised learning. This paper is significant because it introduces a method that considers output information to derive more accurate and appropriate clusters. The algorithm is applied to fuzzy system structure identification giving better accuracy, and fewer fuzzy rules and parameters.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
2
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-