Sentence examples for approaches perform very from inspiring English sources

Although most graph-based semi-supervised dimensionality reduction approaches perform very well on clean data sets, they usually cannot construct a faithful graph which plays an important role in getting a good performance, when performing on the high dimensional, sparse or noisy data.

Although SRC-based approaches perform very well in many situations, the execution time in SRC-based approaches is more than that in LRC-based approaches.

It can also be seen from Table 2 that if ϕ t changes from a smaller number to a larger number, then these two test approaches perform very well.

We apply fuzzy logic system (FLS) to automatic target detection based on the AC power values from DCT. Simulation results show that our MLE-DCT-FLS and soft-max-DCT-FLS approaches perform very well in the radar sensor network target detection, whereas the existing 2D construction algorithm does not work in this study.

We showed than both approaches perform very similar when predicting long, unmethylated regions or polycomb sites.

Most of the approaches perform very similarly in this case, with AdaBoost having slightly reduced power compared with others, which is similar to the additive model.

We applied fuzzy logic system (FLS) to automatic target detection based on the AC power values from DCT. Simulation results showed that our MLE-DCT-FLS and soft-max-DCT-FLS approaches performed very well in the radar sensor network target detection, whereas the existing 2-D construction algorithm could not work in this study.

Nevertheless, the one-step approaches performed very well for scenarios 3 and 5, with average power ranging from 0.986 to 1.0 and 0.925 to 1.0, respectively.

Numerical experiments indicate that this new one-level approach performs very well.

Experiments show that our approach performs very well and has the potential to be used in the garment design industry.

Our experimental results show that our approach performs very well, being able to reconstruct with very high accuracy extremely complicated shapes, unfeasible for reconstruction with current methods.