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In the previous section, we have investigated the persistence of the solution to model (9).
Assume that the vector (x in mathbb {R}^{n}) is a solution to model (9).
Motivated by [14], we can prove the global existence of a solution to model (5).
The moment estimation of the solution to model (8) will be investigated as the first part of this section.
Moreover, the pth moment in time average of the solution to model (8) is discussed in Theorem 4.2.
Conversely, assume optimal solution to Model 6 is obtained at (left( {varvec{u},varvec{v},varvec{z}} right)).
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Neural regression provides a rapid solution to modeling complex systems with minimal computation effort.
The exact analytical solutions to model equations are derived.
A further analysis has been carried out to determine the sensitivity of solutions to model parameters.
On the other hand, if ∥x∥0>s then all solutions to model (7) do not satisfy the consistency constraint.
After designing the model, the maximum length of elements was set at 0.4 μm; this was sufficient to provide accurate solutions to model at that scale.
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