Title :
An evolutionary approach to system-level fault diagnosis
Author :
Yang, Hui ; Elhadef, Mourad ; Nayak, Amiya ; Yang, Xiaofan
Author_Institution :
Coll. of Comput. Sci., Chongqing Univ., Chongqing
Abstract :
Artificial immune systems (AIS) have been widely applied to many fields such as data analysis, multimodal function optimization, error detection, etc. In this paper, we show how AIS can be used for system-level fault diagnosis. Experimental results from a thorough simulation study and theoretical analysis demonstrate the effectiveness of the AIS-based diagnosis approach for different small and large systems in both the worst and average cases, making it a viable addition to the existing diagnosis algorithms.
Keywords :
data analysis; evolutionary computation; fault diagnosis; multiprocessing systems; AIS-based diagnosis approach; artificial immune systems; data analysis; error detection; evolutionary approach; multimodal function optimization; system-level fault diagnosis; Artificial immune systems; Computer errors; Computer science; Data analysis; Data engineering; Educational institutions; Fault detection; Fault diagnosis; Information technology; System testing; Artificial immune systems; multiprocessor and multicomputer systems; system-level fault diagnosis;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983108
