With the aim of a more effective representation of reliability assessment for real industry, in the last years concepts like dynamic fault trees (DFT) have gained the interest of many researchers and engineers (dealing with problems concerning safety management, design and development of new products, decision analysis and project management, maintenance of industrial plant, etc).
Polar representations of reliability and redundancy are obtained for different encountered sea states, ship speeds and headings, covering a large spectrum of operational conditions.
The representation of system reliability is parameterized by the loss of load probability (LOLP) and energy shortages [33].
Limited taxonomic representation decreases the reliability and precision of a phylogeny, in turn limiting interpretations on dating, biogeography, and cladogenesis.
Instead, we used the actual study data to calculate values for the SEM, to give an approximate representation of the reliability of the data.
The key idea of the proposed approach is the construction of an approximate representation of the structural reliability (i.e. a meta-model for reliability).
Essentially the introduction of reliability of representation and instantaneous transmission.
The method exploits the ordering statistics representation property of the reliability plot, which is shown to approximately obey an orthogonal hyperbolic pattern.
The neural network representation facilitates the estimation of reliability by Monte Carlo simulation, and the reliability achieved in each performance level, for a specific combination of the design parameters, is itself represented with a neural network.
The phase type model is flexible enough to comprise many realistic situations, and also manages to yield the explicit matrix representations of the system reliability measures.
