Extração de conhecimento em forma de regras difusas a partir de mapas auto-organizáveis de Kohonen: aplicação em diagnóstico de faltas incipientes em transformadores

Abstract

Despite the many advantages offered by the artificial neural networks, some limitations still prevent their widespread use, especially in applications that require making decisions essential to ensure safety in environments such as in Power Systems. A major limitation of artificial neural networks with respect to the inability of these networks is to explain how to arrive at certain decisions. This explanation must be humanly understandable. Thus, this paper proposes a method for extracting fuzzy rules from Kohonen self-organizing map, designing a fuzzy inference system capable of explaining the decisions taken by the map. To verify its effectiveness, the method is applied to solve the problem of classification for the diagnosis of incipient faults in power transformers used.