Name
Abstract | ||
|---|---|---|
The antecedent and consequent parts of a first-order evolving intelligent system (EIS) determine the validity of the learning results and overall system performance. Nonetheless, the state-of-the-art techniques mostly stress on the novelty from the system identification point of view but pay less attention to the optimality of the learned parameters. Using the recently introduced autonomous learni... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCYB.2020.2967462 | IEEE Transactions on Cybernetics |
Keywords | DocType | Volume |
Optimization,Silicon,Fuzzy systems,Particle swarm optimization,Intelligent systems,Search problems,Prediction algorithms | Journal | 51 |
Issue | ISSN | Citations |
11 | 2168-2267 | 3 |
PageRank | References | Authors |
0.40 | 40 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaowei Gu | 1 | 99 | 10.96 |
| Qiang Shen | 2 | 28 | 5.36 |
| Plamen Angelov | 3 | 954 | 67.44 |