Please use this identifier to cite or link to this item:
https://open.uns.ac.rs/handle/123456789/12463
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Djukanovic M. | en |
dc.contributor.author | Bekut, Duško | en |
dc.contributor.author | Sobajic D. | en |
dc.contributor.author | Pao Y. | en |
dc.date.accessioned | 2020-03-03T14:48:35Z | - |
dc.date.available | 2020-03-03T14:48:35Z | - |
dc.date.issued | 1992-01-01 | en |
dc.identifier.issn | 3787796 | en |
dc.identifier.uri | https://open.uns.ac.rs/handle/123456789/12463 | - |
dc.description.abstract | In this paper we present a new method for short-circuit studies in three-phase systems based on the use of supervised learning neural net technology and the adaptive pattern recognition concept. Neural nets are used to assess the essential characteristics of short-circuit currents. The main motivation is to exploit generalization capabilities of neural nets to interpolate between training data, and thus to allow fast and direct assessment of short-circuit currents in cases of changing network topology and parameters. We present the results obtained in computer simulations using the example of a power system. © 1992. | en |
dc.relation.ispartof | Electric Power Systems Research | en |
dc.title | Neural network based calculation of short-circuit currents in three-phase systems | en |
dc.type | Journal/Magazine Article | en |
dc.identifier.doi | 10.1016/0378-7796(92)90044-2 | en |
dc.identifier.scopus | 2-s2.0-0026891460 | en |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/0026891460 | en |
dc.relation.lastpage | 53 | en |
dc.relation.firstpage | 49 | en |
dc.relation.issue | 1 | en |
dc.relation.volume | 24 | en |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Fakultet tehničkih nauka, Departman za energetiku, elektroniku i telekomunikacije | - |
crisitem.author.parentorg | Fakultet tehničkih nauka | - |
Appears in Collections: | FTN Publikacije/Publications |
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