What is it about?
The problem of reliability analysis of phased-mission system has been studied in literature over the past three decades. However, the existing methods are inefficient when PMSs are large in scale. We have proposed a model compressed storage scheme and a reliability computing methods based on Krylov subspace. The performance and the effiectiveness of the proposed methods are demonstrated through a typical example.
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Why is it important?
In this paper, a relationship is derived to compute the non-zero elements of the transition rate matrix (TRM) of a Markov model. Moreover, a TRM compressed storage scheme (TRMCS) is proposed, and a method to solve the state probability vector using the Krylov subspace is proposed. Example shows that the method combined with TRMCS and Krylov subspace achieves a remarkable storage and computation efficiency.
Perspectives
Application fo the Markov approach in the reliability analysis of phased-mission system may encounter the problem of state space explosion. We proposed a method combined with compressed storage and the Krylov subspace for solving a large PMS under Markov environment. Our work is important for PMS reliability analysis and application of Markov approach.
Hua Yan
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This page is a summary of: Reliability computing method combined with compressed storage and Krylov subspace for phased-mission system, Communication in Statistics- Theory and Methods, September 2016, Taylor & Francis,
DOI: 10.1080/03610926.2016.1228966.
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