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This paper proposes an algorithm for pruning ELM networks by using regularized regression methods, thus obtaining a suitable number of the hidden nodes in the network architecture.
This way, these techniques can be used in tandem with other non-selective methods, thus obtaining efficiency and cost effectiveness.
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The EDG methods are thus obtained from the hybridizable discontinuous Galerkin (HDG) method by requiring the approximate trace to belong to smaller approximation spaces than the one in the HDG method.
A stochastic algorithm to solve the coupled flow and mass transport inverse problem is combined with a stochastic management approach to develop methods for integrating uncertainty; thus obtaining more reliable policies on groundwater nitrate pollution control from agriculture.
The CI in the height method is thus obtained as the ratio (I200 − IAM)/ I200.
Then, for all methods, we ranked these genes, thus obtaining ranking lists of genes.
In the other case, we reduce the reaction scheme in Equation (1) to a single S → P reaction but the waiting times are computed (using our method) according to Equation (3), thus obtaining a non-Markovian model.
The geometry optimization has been performed using DFT method and geometrical parameters thus obtained for the complexes have been compared with their single crystal XRD structures.
The specimens were processed by modified Petroff's method and the deposits thus obtained were washed with 0.067M phosphate buffer saline at pH 7.0 to neutralize the samples.
To overcome this problem and thus obtain a method that is applicable to large NGS datasets, we employ a special kind of PCA called kernel-PCA which is known to scale well for large numbers of variables (SNPs in our case) (Murphy 2012).
We modify the proximal-gradient algorithm based on the viscosity proximation method; thus, we obtain strong convergence of results in [11].
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