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Mathematical problems raised by applications of multi-state system model in system failure engineering are addressed.
Subsequently, a simple dynamic clustering algorithm is proposed in order to verify the effects of clustering model in system performance.
We rely on a long-term market simulation model in system dynamics that characterizes expansion decision in a competitive regime.
We use the proposed interference model in system level simulation and quantify the effect of the RS interference in an indoor environment.
Last but by no means least is Jerome Vanclay's (2014) highly interesting paper "Unsuspected implications arising from assumptions in simulations: Insights from recasting a forest growth model in system dynamics".
For given list of the test error patterns E in (8), and assuming the system model in "System model" section with asymptotically large SNR, the probability P I = Pr c ̂ = 0 | c ̂ 0 ∈ E is dominated by the error events corresponding to the error patterns with the smallest Hamming distances.
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Every kinetic model in systems biology is valuable and deserves attention just because they aim at providing mechanistic explanations which the unsupervised data analysis methods in statistics lack.
In this paper, procedures of outage modeling in system state selections have been modified using the updated outage model considering component failure risks.
Philosophical caveats regarding models in system ergonomics are discussed, as well as the relation to scientific method.
Nowadays most models in systems engineering are created with the UML as standardized set of notations.
One area where combined explanations for developmental phenomena are being analyzed pertains to mechanism descriptions and mathematical modeling in systems biology (Brigandt 2013; Fagan 2013).
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