Name
Title | ||
|---|---|---|
A Data Driven Knowledge Acquisition Method and Its Application in Power System Dynamic Stability Assessment |
Abstract | ||
|---|---|---|
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Bayesian approach to a segmentation model based on the switching linear Gaussian ... |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICMLA.2008.149 | ICMLA |
Keywords | Field | DocType |
time-series segmentation,bayesian approach,power system dynamic stability,data driven knowledge acquisition,unsupervised scenario,linear gaussian,fundamental problem,segmentation model,power systems,feature selection,algorithm design and analysis,decision trees,stability analysis,knowledge extraction,feature space,prediction algorithms,data mining,decision tree | Data mining,Decision tree,Feature vector,Algorithm design,Data-driven,Feature selection,Computer science,Electric power system,Stability assessment,Artificial intelligence,Knowledge extraction,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lin Guan | 1 | 0 | 0.34 |
| Tong-Wen Wang | 2 | 10 | 1.21 |
| Yao Zhang | 3 | 45 | 12.56 |
| Li-jun Zhang | 4 | 0 | 0.34 |