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dc.date.accessioned 2008-05-20T21:22:21Z
dc.date.available 2008-05-20T03:00:00Z
dc.date.issued 2006-10
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/9541
dc.description.abstract It is observed that conventional techniques to analyse the steady state analysis of Self-Excited Induction Generator (SEIG) involve cumbersome mathematical procedures. In this paper an Artificial Intelligence (AI) technique has been used to analyse the behaviour of Self-Excited Induction Generator, which does not require rigorous modelling as required in conventional techniques. Proposed Artificial Neural Network (ANN) model has been implemented to predict the effect of speed, capacitance and load on generated voltage and frequency of SEIG. Experimental data is used for the training of ANN. Results obtained from the trained ANN are found to be in close agreement with the experimental results. en
dc.format.extent 73-79 es
dc.language en es
dc.subject Connectionism and neural nets es
dc.subject ARTIFICIAL INTELLIGENCE es
dc.title Application of Artificial Neural Network for Analysis of Self-Excited Induction Generator en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct06-3.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Khela, Raja Singh es
sedici.creator.person Bansal, Raj Kumar es
sedici.creator.person Sandhu, K. S. es
sedici.creator.person Goel, Ashok Kumar es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc/3.0/
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000000561 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 6, no. 2 es


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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)