ON IMPLICATION AND INDISTINGUISHABILITY IN THE SETTING OF FUZZY LOGIC**la fond remembrance of Xarier Domingo.

Trillas, Enric; Valverde, Llorenç

doi:10.1016/b978-1-4832-1450-4.50013-4

Cited by 47 publications

(39 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It is immediate to see that 0 is the only membership function which is strong-self-contradictory but F (E) is so large that whenever a strong negation N g is considered, it is possible to find weak-self-contradictory elements and (N g , x)-local self-contradictory membership functions. Such elements are easily identified by means of the following observation: (4) holds if and only if (x)-n g (the fixed point of N g ) and therefore (3) holds if and only if -n g , i.e., all functions below n g are weak-self-contradictory. What is worse is that, whenever sup + (x) " x3E,:1 then, there exist strong negations N g which make a weak-self-contradictory membership function.…”

Section: Selfcontradiction In Fuzzy Sets Theorymentioning

confidence: 99%

On contradiction in fuzzy logic

Trillas

Alsina

Jacas

1999

Soft Computing - A Fusion of Foundations, Methodologies and App

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Selfcontradiction In Fuzzy Sets Theorymentioning

confidence: 99%

On contradiction in fuzzy logic

Trillas

Alsina

Jacas

1999

Soft Computing - A Fusion of Foundations, Methodologies and App

Self Cite

View full text Add to dashboard Cite

show abstract

“…The process of making the information uniform involves the comparison between fuzzy sets representing the semantics of the initial terms assessed in Si and the fuzzy sets of the linguistic terms of the BLTS. Comparisons are usually carried out by means of a measure of comparison, that depending on the framework, the measure of comparison can have different forms [13,14,25,37,38,47]. We focus on measures of comparison which evaluate the resemblance or likeness of two objects (fuzzy sets in our case).…”

Section: Making the Information Uniformmentioning

confidence: 99%

A Multi-granular Linguistic Decision Model for Evaluating the Quality of Network Services

Herrera

Herrera‐Viedma

Martínez

et al. 2004

Intelligent Sensory Evaluation

View full text Add to dashboard Cite

Summary. The fuzzy linguistic approach has been applied successfully to many problems dealing with qualitative aspects that are assessed by means of linguistic terms. The use of linguistic information implies in most cases the need for using fusion processes to obtain aggregated values that summarize the input information. One important limitation of the fuzzy linguistic approach appears when fusion processes are applied to problems in which the linguistic information is assessed in linguistic term sets with different granularity of uncertainty, i.e., different cardinality; this type of information is denoted as multi-granular linguistic information. This limitation consists of the difficulty in dealing with this type of information in fusion processes due to the fact that there is no standard normalization process for this type of information, as in the numerical domain.In this contribution, taking as base the 2-tuple fuzzy linguistic representation model and its computational technique, we shall present a method for easily dealing with multi-granular linguistic information in fusion processes. Afterwards, we shall apply this fusion method to a decision process in a multi-expert decision-making (MEDM) problem with multi-granular linguistic information, that evaluates the quality of network services from different Operative Systems.

show abstract

“…There exists another class of operators that can be used to interpret the logical implication based upon the residuation process [3,[11][12][13]. In the following we shall use R(a, b) to indicate this class of operations,…”

Section: Residuation Based Interpretationsmentioning

confidence: 99%

On the interpretation of fuzzy if then rules

Yager

1996

Appl Intell

View full text Add to dashboard Cite

The basic algorithm for reasoning in the fuzzy systems modeling method is introduced. Two classes of operators for interpreting the rules in these models are described, the Mamdani-Zadeh operator and the logical operator. The basic characteristics of these operators are presented and it is shown that the two classes of operators are distinguished by their response to a zero firing level. A class of Mamdani-Zadeh operators based upon the residuation operation is presented. A comparison is made between the performance of these residuation based Mamdani-Zadeh operators and the standard Mamdani-Zadeh operators derived from the t-norm. A new class of Mamdani-Zadeh operators based upon a generalization of the bounded difference is presented.

show abstract

ON IMPLICATION AND INDISTINGUISHABILITY IN THE SETTING OF FUZZY LOGIC**la fond remembrance of Xarier Domingo.

Cited by 47 publications

References 10 publications

On contradiction in fuzzy logic

On contradiction in fuzzy logic

A Multi-granular Linguistic Decision Model for Evaluating the Quality of Network Services

On the interpretation of fuzzy if then rules

Contact Info

Product

Resources

About