Name
Title | ||
|---|---|---|
Stacked-Structure-Based Hierarchical Takagi-Sugeno-Kang Fuzzy Classification Through Feature Augmentation. |
Abstract | ||
|---|---|---|
In this paper, a new stacked-structure-based hierarchical Takagi-Sugeno-Kang (TSK) fuzzy classifier called SHFA-TSK-FC with both promising performance and high interpretability is proposed to tackle with the shortcoming of the existing hierarchical fuzzy classifiers in interpreting the outputs and fuzzy rules of intermediate layers. In order to achieve the enhanced classification performance, each... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TETCI.2017.2761915 | IEEE Transactions on Emerging Topics in Computational Intelligence |
Keywords | DocType | Volume |
Fuzzy sets,Learning systems,Computational intelligence,Takagi-Sugeno model,Feature extraction,Classification | Journal | 1 |
Issue | Citations | PageRank |
6 | 3 | 0.37 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ta Zhou | 1 | 29 | 1.40 |
| Hisao Ishibuchi | 2 | 7385 | 503.41 |
| Shitong Wang | 3 | 1485 | 109.13 |