Checking the coherence and redundancy of fuzzy knowledge bases

Fuzzy Rule Iterative Feature Selection (FRIFS) with Respect to the Choquet Integral Apply to Fabric Defect Recognition

“…This inference mechanism gives an interpretation and semantics, which differ from mechanisms using implication. In particular, it assures the consistency of the rule base [18]. If no information is processed that is the input space is not covered by rule set; the output gives an "unknown defect".The chosen classifier is based on Ishibuchi's algorithm which provides an automatic rule generation step [19].…”

“…The iterative version of the method [21] is used here because it supports the rule of having the maximum response. The expert must prepare defective sample sets to generate the fuzzy rules via an automatic rule generation algorithm [18].…”

On Perception-based Logical Deduction and Its Variants

“…The only exception in favor of the implicative approach represented byR is an existence of a sort of "built-in" consistency checking mechanism [10], which uses the definition of the notion of coherence [11]. This only underlines the fact that implicative rules are not only more appropriate semantical model with respect to the syntactical form of the IF-THEN rules (1), but at least equally or even more practical than the Mamdani-Assilian rules that are used significantly more often [12].…”

“…Let A i , i ∈ N n , be one of the antecedent fuzzy sets of LD. Then we will denote by C i the result of r P bLD (11) for A 0 = A i . Sketch of the proof: According to (10),…”

A Fuzzy-Rule-Based Model for Handling Contextual Preference Queries

“…. , n} denotes a set of n fuzzy rules (where U and V are the domains of the variables X and Y respectively), the degree of coherence ‡ of S is defined as 24 :…”