Name
Title | ||
|---|---|---|
Constructing ANFIS With Sparse Data Through Group-Based Rule Interpolation: An Evolutionary Approach |
Abstract | ||
|---|---|---|
An adaptive-network-based fuzzy inference system (ANFIS) offers a popular and powerful fuzzy inference mechanism. As with many other advanced data-driven techniques, developing an effective ANFIS typically requires sufficient training data. However, in many real-world applications, it is not always straightforward to obtain a large amount of representative data that cover the entire problem space ... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TFUZZ.2021.3049949 | IEEE Transactions on Fuzzy Systems |
Keywords | DocType | Volume |
Interpolation,Training data,Genetic algorithms,Data models,Fuzzy logic,Biological cells,Statistics | Journal | 30 |
Issue | ISSN | Citations |
4 | 1063-6706 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jing Yang | 1 | 158 | 58.81 |
| Changjing Shang | 2 | 212 | 34.92 |
| Ying Li | 3 | 0 | 0.34 |
| Fangyi Li | 4 | 24 | 6.13 |
| Liang Shen | 5 | 0 | 0.34 |
| Qiang Shen | 6 | 864 | 55.09 |