In our previous work [11] we found that ASNN [44] and SVM [45] methods provided significantly higher accuracy of MP predictions compared to other tested methods while the accuracy of models developed with both methods was similar.
Yuan et al. (2012) evaluated six commonly used DNA extraction methods on a mock microbial community that contained 11 different human-associated bacteria, and showed that each of the six methods provided significantly different 16S rRNA gene sequencing profiles of the mock microbial community.
We can see that similarly to the modeling results, the particle projection and power spectrum method provide significantly better results for this type of sample.
It was found that the proposed cold recycling method provided significantly better overall performance than the conventional method.
The proposed method provides significantly improved closed loop performances when compared to the methods in the literature.
Simulation shows that compared to the widely used integral control method, the proposed method provides significantly improved disturbance rejection and robustness against load variation.
The preliminary results indicate that the proposed method provides significantly better results compared with other high performing algorithms in the literature.
From the verification results, it can be seen that the proposed method provides significantly better estimation of SWCC for the granular soils with different initial dry densities than the Fredlund and Xing equation.
These results confirm that our method provides significantly improved estimates over raw search results, and these can either be used directly for large-scale (departmental or university) analysis or further refined manually to quickly give accurate publication-citation records.
