A linear approach to determining an SVM-based fault locator's optimal parameters

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1. Verfasser: Lucas Pérez Hernández
Format: Artículo científico
Sprache:en
Veröffentlicht: Universidad Nacional de Colombia 2009
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author Lucas Pérez Hernández
author_facet Lucas Pérez Hernández
contents A linear approach to determining an SVM-based fault locator's optimal parameters Lucas Pérez Hernández Juan Mora Flórez Juan Bedoya Cebayos Ingeniería fault location linear programming support vector machine Euclidean distance norm The setting up process for support vector machines (SVM) is discussed in this paper. Such settings are normally obtained from exhaustive testing of SVM, settled on by using several configuration parameter values and evaluating performance by using techniques such as cross validation. The linear approach presented in this paper is based on redefining the classical SVM second- order objective function. Better setting parameters were obtained by using low computational cost methodology for resolving new linear optimisation. The proposed approach was applied to a typical classification problem regarding fault location in power distribution systems; the results so obtained were compared to those obtained using classical methodology. An 80% improvement was achieved in mean error when estimating fault location and 56% reduction in the computing time needed for obtaining the best results when using classical approaches. 2009 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64329111 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.1 Vol.29
format Artículo científico
id redalyc_64329111
institution Redalyc
language en
publishDate 2009
publisher Universidad Nacional de Colombia
spellingShingle A linear approach to determining an SVM-based fault locator's optimal parameters
Lucas Pérez Hernández
Ingeniería
fault location
linear programming
support vector machine
Euclidean distance norm
A linear approach to determining an SVM-based fault locator's optimal parameters Lucas Pérez Hernández Juan Mora Flórez Juan Bedoya Cebayos Ingeniería fault location linear programming support vector machine Euclidean distance norm The setting up process for support vector machines (SVM) is discussed in this paper. Such settings are normally obtained from exhaustive testing of SVM, settled on by using several configuration parameter values and evaluating performance by using techniques such as cross validation. The linear approach presented in this paper is based on redefining the classical SVM second- order objective function. Better setting parameters were obtained by using low computational cost methodology for resolving new linear optimisation. The proposed approach was applied to a typical classification problem regarding fault location in power distribution systems; the results so obtained were compared to those obtained using classical methodology. An 80% improvement was achieved in mean error when estimating fault location and 56% reduction in the computing time needed for obtaining the best results when using classical approaches. 2009 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64329111 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.1 Vol.29
title A linear approach to determining an SVM-based fault locator's optimal parameters
topic Ingeniería
fault location
linear programming
support vector machine
Euclidean distance norm
url https://www.redalyc.org/articulo.oa?id=64329111