Sentence examples for using the extracted rules from inspiring English sources

SOFLCs using the extracted rules are also shown to outperform those using expert derived rules in terms of improved control stability.

Similarly, we hypothesized that SOFLCs using the extracted rule-bases would perform better than those using expert derived rule-bases.

During the simulations we occasionally found that the type-1 SOFLC using the extracted rule-base was less stable compared to using the expert derived rules.

In order to make a precise analysis, we again applied a one-tailed Wilcoxon signed-rank test on the hypothesis that SOFLCs using the extracted rule-base would perform better than those using the expert derived rule-base.

In the second step, MCDA is used to evaluate the extracted rules according to the decision makers' preferences in order to reduce the large number of rules, and shows only the most relevant.

This technique is enhanced using a grouped matrix, by grouping the extracted rules using clustering; an example of a grouped matrix-based visualization is given in Fig. 9.

In order to recognise a number plate, all the characters contained are tested one by one using the extracted set of rules by RULES-3.

To visualize the extracted rules, we use arulesViz [30] as an R package extension; this implements several known and novel visualization techniques such as matrix-, group-, and graph-based visualization.

P values for each of the extracted rules were used to allow ranking of the ARs.

During our experiments, we also recorded rules' firing percentage and the result showed that the extracted rule-base used a subset of fewer more concentrated rules that contributed more frequently and consistently over the inference operations, resulting in better control stability than the expert derived rule-base.

However, the extracted rule-base is still able to use fewer rules to reach the same kind of steady state error performance as the expert derived rule-base.