Evaluación comparativa de tres métodos de clasificación aplicados al problema de la localización de fallas de cortocircuito en sistemas de distribución de energía eléctrica
Abstract
En este artículo se analiza y compara el desempeño de las Máquinas de Soporte Vectorial (SVM), el Algoritmo de Aprendizaje para Análisis de Datos Multivariable (LAMDA) y las Mezclas Finitas (MF), técnicas del campo de la computación suave, aplicadas al problema de la localización de fallas en sistemas de distribución. Metodológicamente, el sistema de distribución es subdividido en varias zonas, y mediante la aplicación de cada una de las técnicas propuestas, se identifica la zona en falla. Como resultado, se obtienen los índices de precisión para cada técnica, alcanzando valores superiores a 90% en el caso de las SVM.Downloads
Downloads
-
Vistas(Views): 533
- PDF (Español (España)) Descargas(Downloads): 469
Published
How to Cite
Issue
Section
License
Copyrights
The journal is free open access. The papers are published under the Creative Commons Attribution / Attribution-NonCommercial-NoDerivatives 4.0 International - CC BY-NC-ND 4.0 license. For this reason, the author or authors of a manuscript accepted for publication will yield all the economic rights to the Universidad Tecnológica of Pereira free of charge, taking into account the following:
In the event that the submitted manuscript is accepted for publication, the authors must grant permission to the journal, in unlimited time, to reproduce, to edit, distribute, exhibit and publish anywhere, either by means printed, electronic, databases, repositories, optical discs, Internet or any other required medium. In all cases, the journal preserves the obligation to respect, the moral rights of the authors, contained in article 30 of Law 23 of 1982 of the Government Colombian.
The transferors using ASSIGNMENT OF PATRIMONIAL RIGHTS letter declare that all the material that is part of the article is entirely free of copyright. Therefore, the authors are responsible for any litigation or related claim to intellectual property rights. They exonerate of all responsibility to the Universidad Tecnológica of Pereira (publishing entity) and the Scientia et Technica journal. Likewise, the authors accept that the work presented will be distributed in free open access, safeguarding copyright under the Creative Commons Attribution / Recognition-NonCommercial-NoDerivatives 4.0 International - https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es license.