Comparison of competitive learning for SOM used in classification of partial discharge

Authors:
Rubén Jaramillo-Vacio;Alberto Ochoa-Zezzatti;Armando Rios-Lira
Affiliations:
Comisión Federal de Electricidad-Laboratorio de Pruebas a Equipos y Materiales (LAPEM), Mexico and Centro de Innovación Aplicada en Tecnologías Competitivas (CIATEC), Mexico;Universidad Autónoma de Ciudad Juárez, Mexico;Instituto Tecnológico de Celaya, Mexico
Venue:
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Year:
2012

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Abstract

This paper shows different competitive learning algorithms for Self Organizing Map (SOM) and are experimentally compared, the characterization of the obtainable results in terms of quality of SOM. The competitive learning algorithms showed to SOM algorithm are Winner-takes-all, Frequency Sensitive Competitive Learning and Rival Penalized Competitive Learning. As a case study: the performance in classification of partial discharge on power cables.