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As a consequence, the proposed approach is highly efficient and is applicable for solving problems involving large number of stochastic dimensions.
SVR is a novel learning methodology based upon statistical learning theory which is applicable for solving the complex non-linear regression estimation problems (Asoodeh et al. 2014a, b, c; Bagheripour et al. 2015).
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This method can be applicable for solving the problem of multi factor complexity and uncertainty.
RCNet is applicable for various industrial applications.
Therefore, the existing solutions do not actually solve the motivating scenario, when the scheme is applicable for cloud computing.
Such problem can be solved by removing and incinerating the peat for generating peat ash which is applicable for stabilization of the compacted clay.
This same approach is applicable for collaboration.
This method is applicable for pairwise comparisons.
This method is applicable for linear analysis.
Similar procedure is applicable for other parameters.
This integrated geodynamic-architectural approach is applicable to solving structural-event histories in other polydeformed terrains.
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