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We summarize all the rules in Table 1.
The compensator factor λ is calculated using fuzzy rules in Table 2.
In each time step, all sites are updated according to the transition rules in Table 2.
According to the fuzzy logic rules in Table 1, the priority of each node is obtained by layer.
By induction on the structure of the sequential process s and then by induction on the rules in Table 9.
With this knowledge, the fuzzy rules in Table 2 are initially derived by trial and error method.
Similar(38)
The problem of missing grapheme-to-phoneme conversion rules in tables has been solved by adding new conversion rules to the existing tables.
Another algorithm, called ConnectionBlockQ [30], is capable of doing mining association rules in tables having quantitative attributes, by means of transforming these data into classes or range of values.
A selection of cluster features are shown ranked by the information gain of the corresponding single-attribute rule in Table 2.
Information on the number of records to which each rule applies – that is, for which the antecedents are true (Instances) – and the proportion of those records for which the entire rule is true (Confidence) is given in parenthesis for each rule in Table 2.
The fuzzy rule base consists of a series of fuzzy rules shown in Table 1.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com