Random Validation and Fault Detection Method in Systems Implementations

Publisher:
IEEE
Publication Type:
Conference Proceeding
Citation:
13th International Conference Intelligent Systems Design and Applications, 2014, pp. 172 - 176
Issue Date:
2014-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnailrandom validation.pdf Published version223.26 kB
Adobe PDF
The problematic absence of a structured technique which in its presence ensures complex infrastructure implementations and software deployment focus on how to utilize prior knowledge of existing infrastructure and on how to apply the information obtained from the preceding and historical outcomes in achieving successful validation cases, has become the central point of discussion in this paper. The concept of Markov Process and Chain validation is based on the BAYESIAN approach to parametric models for implementations which can employ prior knowledge, even skills and preceding outcomes for their parameter estimation. This paper proposes an important validation technique drawn from Markov Process and Monte Carlo method and presents statistical analysis to examine the effectiveness of Markov Chain with basic random validation.
Please use this identifier to cite or link to this item: