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Lietuvos Matematikos Rinkinys
Article . 2008 . Peer-reviewed
License: CC BY
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Lietuvos Matematikos Rinkinys
Article
License: CC BY
Data sources: UnpayWall
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Lietuvos Matematikos Rinkinys
Article . 2008
Data sources: DOAJ
https://doi.org/10.2495/risk08...
Article . 2008 . Peer-reviewed
Data sources: Crossref
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Modelling of the node immunity change process in a network system

Authors: Benas Jokšas; Juozas Augutis; Inga Žutautaitė-Šeputienė;

Modelling of the node immunity change process in a network system

Abstract

In this paper we analyze the additive hazard distribution modelling in the network system with non-constant nodes’ immunities. Nodes’ immunities depend on number of cycle and unknown parameter that is defined as random variable. Bayesian approach is applied for the updating of the estimate of this random variable. In this study we are interested in how many cycles can system work under influence of the hazard in the network or how many cycles are required to reduce amount of the nodes’ hazard to the safe level. Obtained results can be used in the prediction of system’ lifetime and accident analysis. Numerical experiment was performed to illustrate application of developed algorithm.

Keywords

Bayesian approach, QA1-939, non-constant immunity modelling, Mathematics

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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
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