Name
Title | ||
|---|---|---|
Incremental Rule Splitting in Generalized Evolving Fuzzy Systems for Autonomous Drift Compensation. |
Abstract | ||
|---|---|---|
Gradual drifts in data streams are usually hard to detect and often do not necessarily trigger the evolution of new fuzzy rules during model adaptation steps in order to represent the new, drifted data distribution(s) appropriately in the fuzzy model. Over time, they thus lead to oversized rules with untypically large local errors (typically also worsening the global model error), as representing ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TFUZZ.2017.2753727 | IEEE Transactions on Fuzzy Systems |
Keywords | Field | DocType |
Adaptation models,Fuzzy systems,Data models,Predictive models,Measurement uncertainty,Shape,Engines | Data modeling,Errors-in-variables models,Data stream mining,Control theory,Fuzzy logic,Outlier,Robustness (computer science),Artificial intelligence,Covariance matrix,Fuzzy control system,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
26 | 4 | 1063-6706 |
Citations | PageRank | References |
19 | 0.60 | 25 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Edwin Lughofer | 1 | 1940 | 99.72 |
| Mahardhika Pratama | 2 | 702 | 50.02 |
| Igor Skrjanc | 3 | 354 | 52.47 |