Sentence examples for using the fuzzy algorithm from inspiring English sources

The proposed GRAMAKA performed best, providing an improvement of 2.9 29.9 %, which is better than that, 1.1 11.2 %, achieved using the fuzzy algorithm.

Table 4 presents the throughput improvements that are achieved using the fuzzy algorithm and the GRAMAKA scheme over the throughput obtained knapsack approach for video traffic (VBR).

Table 3 presents the improvements in throughput that are obtained using the fuzzy algorithm and GRAMAKA scheme over the throughput that is obtained using the knapsack approach for voice traffic (CBR).

Table 5 presents the throughput improvements that are achieved using the fuzzy algorithm and the GRAMAKA scheme over the throughput that is obtained using the knapsack approach for data traffic (VBR).

GRAMAKA provides improvements of 2.9 29.9, 50.1 79.2, and 1.63 6.04 %, respectively, which are better than that, 1.1 11.2, 15.1 29.1, and 0.61 1.89 %, achieved using the fuzzy algorithm, in the cases of voice traffic (CBR), video traffic (VBR), and data traffic (VBR), respectively.

Then, the cluster algorithm was run 10 times to generate several clusters solutions that were next merged using the fuzzy clustering algorithm for a final robust cluster solution.

We validated that both positive feedback and negative feedback approach curves obtained using the fuzzy logic algorithm matched well with simulated approach curves for both large microelectrodes (sometimes used for Surface-Interrogation SECM, a = 175 μm) and for conventional SECM ultramicroelectrodes (a = 4.2 μm).

Finally, sentiment values from users in different time periods were selected as original data matrix, using the fuzzy clustering algorithm.

Next, emotional values of 50 users in 10 time periods are selected to make emotion classification analysis for micro-blog users by using the fuzzy clustering algorithm, and F testing method is used to calculate an optimal classification.

The IoC machine, estimating the anesthesia index by using the fuzzy inference algorithm, also shows the EMG bar and burst suppression ration (BSR).

The parameters in both the linear and nonlinear regression models are estimated using the fuzzy evidential EM algorithm, a straightforward fuzzy version of the evidential EM algorithm.