E-resources
-
Soni, Prity; Mondal, Debasmita; Chatterjee, Soumya; Mishra, Pankaj
2022 IEEE International Power and Renewable Energy Conference (IPRECON), 2022-Dec.-16Conference Proceeding
The classification of power quality disturbances (PQDs) is essential for the stability and reliability of the power system. A method to categorize PQD incidents using a recurrence plot (RP) is developed in this work. RP technique is used to transform 1-D PQD into 2-D graphics. PQD events were produced in compliance with IEEE standard 1159-1995 in both single and multiple forms. The 2-D graphics created using RP is fed to the deep learning architectures: Googlenet, ResNet-50 and Alexnet. The features obtained from deep learning were classified using support vector machine, which shows the correct classification of 15 classes with 99.63% accuracy.
Shelf entry
Permalink
- URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
| Year | Impact factor | Edition | Category | Classification | ||||
|---|---|---|---|---|---|---|---|---|
| JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP | |
Select the library membership card:
If the library membership card is not in the list,
add a new one.
DRS, in which the journal is indexed
| Database name | Field | Year |
|---|
| Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
|---|
Source: Personal bibliographies
and: SICRIS
The material is available in full text. If you wish to order the material anyway, click the Continue button.