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http://localhost:8080/xmlui/handle/123456789/3537Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Patil, Rupali R. | - |
| dc.contributor.author | Sohale, Jagruti R | - |
| dc.contributor.author | Kangune, Sujata P. | - |
| dc.date.accessioned | 2022-12-30T06:18:49Z | - |
| dc.date.available | 2022-12-30T06:18:49Z | - |
| dc.date.issued | 2022-07-01 | - |
| dc.identifier.issn | ) 2393-8021 | - |
| dc.identifier.uri | http://192.168.3.232:8080/jspui/handle/123456789/3537 | - |
| dc.description.abstract | Power companies now days are using different techniques for restoration of Power. There are many laid down procedures to be followed for Power restoration. Computer aided system can find more effective ways for power restoration. There are many challenges for power restoration. This paper briefly proves the idea behind the Artificial Neural Network in power restoration. It also describes the types of the Artificial Neural Network, their structures, different learning methods and power restoration methods. The power restoration plans are made by the Artificial Neural Network with the help of the power system restoration plan | en_US |
| dc.subject | Artificial | en_US |
| dc.subject | Neural | en_US |
| dc.subject | Network | en_US |
| dc.subject | Power | en_US |
| dc.subject | Restoration | en_US |
| dc.title | Power system restoring based on Artificial Neural Network | en_US |
| Appears in Collections: | Faculty Publication | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Artificial Neural Network IARJSET.2022.9732 (1).pdf | 288.97 kB | Unknown | View/Open |
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