@inproceedings{9dcfb59db9f048c396143de11ae26b38,
title = "An application of S VM, RBF and MLP with ARD on bushings",
abstract = "This paper examines classification models using three classes of artificial neural networks (ANN). The first ANN uses Support Vector Machine activation functions. The second uses Multiple -layered Perceptron (MLP) activation functions with automatic relevance detection (ARD). And the third uses Radial Basis activation functions (RBF). In this work the decision is taken to remove or leave a bushing in service based on analysis of bushing parameters using RBF, SVM and MLP, The work finds that the RBF converges to a solution faster than both SVM and MLP. The MLP is the best tool of the three for analyzing large amounts of non-parametric non-linear data. MLP is the most accurate of the three networks. ARD reveals that Methane was the most common cause for action on bushings tested using DGA during the two years evaluation period.",
keywords = "Bushing, Diagnosis, Dissolved gas analysis, Multiple layered perceptron, Radial basis, Support vector machines",
author = "Dhlamini, {Sizwe M.} and Tshilidzi Marwala",
year = "2004",
language = "English",
isbn = "0780386442",
series = "2004 IEEE Conference on Cybernetics and Intelligent Systems",
pages = "1253--1258",
booktitle = "2004 IEEE Conference on Cybernetics and Intelligent Systems",
note = "2004 IEEE Conference on Cybernetics and Intelligent Systems ; Conference date: 01-12-2004 Through 03-12-2004",
}