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For this purpose we assigned distributions to all uncertain parameter.
The authors considered demand as the uncertain parameter.
The uncertain parameter is well estimated from the system parameter in the sense of.
Simultaneously the uncertain parameter of the receiver system is also identified.
So, as mentioned above, the type-1 fuzzy model cannot consider b as an uncertain parameter.
The third uncertain parameter in this paper is market demand of final products j.
This realization then is employed to construct random orthogonal basis for each uncertain parameter.
The proposed methodology helps identify the relative importance of each uncertain parameter on the fragility curves.
It also allows appreciation of the role of each uncertain parameter.
Perturbation is introduced to analyze the navigation state errors from each unobservable uncertain parameter.
The first demonstration example is a scalar problem that is linear in the uncertain parameter.
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