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IA para estimación de la tolerancia a fallos en aplicaciones aeroespaciales

Authors: Ruiz Falcó, David;

IA para estimación de la tolerancia a fallos en aplicaciones aeroespaciales

Abstract

La tolerancia a fallos, es decir la capacidad de trabajar de forma correcta aún en presencia de fallos, es un requisito fundamental en los sistemas que operan en entornos afectados por la radiación natural (naves espaciales, satélites, aviones, drones, etc.). Evaluar la fiabilidad de estas aplicaciones es una tarea muy costosa que requiere una enorme cantidad de tiempo de cómputo para la simulación de millones de fallos. El propósito de este proyecto es reducir este problema mediante el desarrollo de un sistema de Inteligencia Artificial. Esta IA debe realizar una estimación a priori de la cobertura frente a fallos a partir del análisis de diversos parámetros de los programas (accesos a memoria, tiempo de vida de los registros, tamaño de las cabeceras).

Country
Spain
Related Organizations
Keywords

Machine learning, Tolerancia a fallos, Arquitectura y Tecnología de Computadores

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green