Abstract—In the traditional fuzzy logic, the expert’s degree of confidence d(A&B) in a complex statement A&B (or A_B) is uniquely determined by his/her degrees of confidence d(A) and d(B) in the statements A and B, as f&(d(A); d(B)) for an appropriate “and”-operation (t-norm). In practice, for the same degrees d(A) and d(B), we may have different degrees d(A&B) depending on the relation between A and B. The best way to take this relation into account is to explicitly elicit the corresponding degrees d(A&B) and d(A_B), i.e., to come up with a “double ” fuzzy set. If we only elicit information about pairs of statements, then we still need to estimate, e.g., the degree d(A&B&C) based on the known values d(A), d(B), ...
In data processing, we often encounter the following problem: Suppose that we have processed the mea...
Experts are often not 100% confident in their statements. One of the most widely used approaches to ...
Abstract—Most applications of fuzzy techniques use piece-wise linear (triangular or trapezoid) membe...
In the traditional fuzzy logic, the expert\u27s degree of confidence d(A & B) in a complex statement...
In the traditional fuzzy logic, we can use and -operations (also known as t-norms) to estimate the ...
In expert systems, we often face a problem of estimating the expert\u27s degree of confidence in a c...
In the traditional (static) fuzzy logic approach, we select an “and”-operation (t-norm) and an “or”-...
Fuzzy techniques are a successful way to handle expert knowledge, enabling us to capture different d...
In many applications of fuzzy logic, to estimate the degree of confidence in a statement A&B, we tak...
In many practical situations, we have several estimates x1, ..., xn of the same quantity x, i.e., es...
In the traditional (static) fuzzy logic approach, we select an and -operation (t-norm) and an or -...
t-norms and t-conorms are the natural connectives “and” and “or” in fuzzy logic. The unit interval w...
We consider here fuzzy quantities, i.e., fuzzy sets without any hypothesisabout normality nor convex...
t-norms and t-conorms are the natural connectives “and” and “or” in fuzzy logic. The unit interval w...
In the traditional fuzzy logic, the experts\u27 degrees of confidence in their statements is describ...
In data processing, we often encounter the following problem: Suppose that we have processed the mea...
Experts are often not 100% confident in their statements. One of the most widely used approaches to ...
Abstract—Most applications of fuzzy techniques use piece-wise linear (triangular or trapezoid) membe...
In the traditional fuzzy logic, the expert\u27s degree of confidence d(A & B) in a complex statement...
In the traditional fuzzy logic, we can use and -operations (also known as t-norms) to estimate the ...
In expert systems, we often face a problem of estimating the expert\u27s degree of confidence in a c...
In the traditional (static) fuzzy logic approach, we select an “and”-operation (t-norm) and an “or”-...
Fuzzy techniques are a successful way to handle expert knowledge, enabling us to capture different d...
In many applications of fuzzy logic, to estimate the degree of confidence in a statement A&B, we tak...
In many practical situations, we have several estimates x1, ..., xn of the same quantity x, i.e., es...
In the traditional (static) fuzzy logic approach, we select an and -operation (t-norm) and an or -...
t-norms and t-conorms are the natural connectives “and” and “or” in fuzzy logic. The unit interval w...
We consider here fuzzy quantities, i.e., fuzzy sets without any hypothesisabout normality nor convex...
t-norms and t-conorms are the natural connectives “and” and “or” in fuzzy logic. The unit interval w...
In the traditional fuzzy logic, the experts\u27 degrees of confidence in their statements is describ...
In data processing, we often encounter the following problem: Suppose that we have processed the mea...
Experts are often not 100% confident in their statements. One of the most widely used approaches to ...
Abstract—Most applications of fuzzy techniques use piece-wise linear (triangular or trapezoid) membe...