The orthogonal nature of the spectral and compositional information provided by Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS) makes them suitable candidates for an optimal combination of their data, thus achieving inferences that are not feasible using a single sensor.
Besides, if the values of some representative attributes cannot be obtained from current environments for inference, some other possible attributes in the same clusters can be used to achieve approximate inference results.
In order to achieve accurate inference, including appropriate correction for multiple comparisons over space, we used permutation-based, non-parametric inference on a voxel-by-voxel basis (Nichols and Holmes, 2002).
It is designed to achieve causal inference by exploiting the natural experiment created by the introduction of gas development, at standard levels of statistical significance, no different than any other non-randomized double blind control trial.
To achieve efficient inference, we apply Rao Blackwellized particle filters at multiple levels of the model hierarchy.
In this paper, a decision support model characterized by its inclusion of fuzzy logic technology to achieve rule inference is proposed.
To avoid statistically insignificant results due to the small size of data sets, it uses bootstrapping to achieve reliable inference and integration.
Using HapMap trio data, at SNPs where one child is homozygotic major, with a minor allele frequency ≤ 0.20, (N = 452684, 65.1%) we achieve 91.9% inference accuracy for sibling genotypes.
Then, the probability inference could be achieved using inference algorithm, such as junction tree method [ 25, 26].
This method achieves an inference time of O N2) by executing each bubble propagation within a small sub-network, i.e., by taking advantage of the knowledge structure.
System identification is achieved through inference of the PMSM's dynamical system behavior, and the deviation of the system's output behavior from the nominal expected behavior yields a measure of the estimated fault.
