@inproceedings{cde53cc07c8143899734216abd402cc0,
title = "Fault types classification using support vector machine (SVM)",
abstract = "Fault type classification is an important task in order to provide reliable electrical service to the customer. In this work, Support Vector Machine (SVM) is used for fault classification in distribution systems. This work proposes an effective fault type classifying method using Support Vector Machine to identify various fault type. Classification and regression analysis of SVM enhances the fault type classification accuracy. The proposed method utilizes voltage sag magnitude and angle measured at the primary substation of a distribution system. The various fault resistance values are used to identify the types of fault. The performance of the proposed method is analyzed using an 18 node distribution system. Results show the accuracy of the proposed method is satisfactory.",
author = "Awalin, \{Lilik J.\} and Kanendra Naidu and Hadi Suyono",
note = "Publisher Copyright: {\textcopyright} 2019 Author(s).; 5th International Conference on Green Design and Manufacture 2019, IConGDM 2019 ; Conference date: 29-04-2019 Through 30-04-2019",
year = "2019",
month = jul,
day = "30",
doi = "10.1063/1.5118140",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Rahim, \{Shayfull Zamree Bin Abd.\} and Abdullah, \{Mohd Mustafa Al-Bakri Bin\}",
booktitle = "5th International Conference on Green Design and Manufacture, IConGDM 2019",
}