A linear approach to determining an SVM-based fault locator's optimal parameters
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| Format: | Artículo científico |
| Sprache: | en |
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Universidad Nacional de Colombia
2009
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| _version_ | 1876487452454027264 |
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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 |