Name
Title | ||
|---|---|---|
Recognition of power quality disturbances using S-transform based ruled decision tree and fuzzy C-means clustering classifiers. |
Abstract | ||
|---|---|---|
•The S-transform based decision tree initialized Fuzzy C-means clustering technique is proposed for recognition of PQ disturbances.•Sum absolute values curve is introduced to increase efficiency of algorithm.•Results of FCM technique are more efficient compared with rule based decision tree.•Validation of results is carried out with 100 data sets of each PQ disturbance with and without noise and comparing with real time results.•Classification accuracy more than 99% is achieved even in the noisy environment. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.asoc.2017.05.061 | Applied Soft Computing |
Keywords | Field | DocType |
Fuzzy C-means clustering initialized by decision tree,Pattern recognition,Power quality,Ruled decision tree,Statistical feature,Stockwell's transform | Decision tree,Synchronization,MATLAB,Pattern recognition,Fuzzy logic,Artificial intelligence,Cluster analysis,S transform,Voltage sag,Machine learning,Mathematics,Real Time Digital Simulator | Journal |
Volume | Issue | ISSN |
59 | C | 1568-4946 |
Citations | PageRank | References |
3 | 0.38 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Om Prakash Mahela | 1 | 4 | 4.46 |
| Abdul Gafoor Shaik | 2 | 3 | 0.38 |
| ShaikAbdul Gafoor | 3 | 3 | 0.38 |