Desarrollo de un algoritmo mediante análisis de aprendizaje automático para la detección de fallos en vehículos M1 con motores de encendido provocado

Abstract

This research paper proposes as its main objective to develop an automatic learning algorithm in order to detect early phase M1 vehicles defects. Therefore, by means of such learning-tools and classification, the system performance data is then analyzed with different kinds of Support Vector Machines (SVMs): including the cubic-classifier and the gaussiano, which function in order to determine reliability.