Fuzzy Sets and Systems

This paper considers updating information and statistical inference based on generalized credal sets. In the first part, we define possible ways of conditioning for generalized credal sets in a finite setting, and its realization based on ...

It is shown that Katětov-Tong insertion theorem continues to hold for normal L-topological spaces and functions with values in appropriately L-topologized tensor product M ⊗ L where L is a complete lattice with an order-reversing involution and M ...

The concept of doubly strong equilibrium is a refinement of the concept of strong Nash equilibrium which represents the most desirable situations for generalized games, where all players get the best among the available outcomes. In this paper, ...

In this note, we discuss the validity of formula (4.54) in Grabisch's book from 2016. This equation expresses the Choquet integral of nonnegative functions w.r.t. a game in the form of linear invertible transform of set functions. However, the ...

As we all know, t-norms can be used to construct fuzzy probabilistic rough set (FPRS). Meanwhile, overlap functions (OFs), as a sort of novel aggregation functions different from t-norms, have shown a flourishing situation in terms of ...

The present paper establishes systematic connections among the first-order correspondents of Sahlqvist modal reduction principles in various relational semantic settings, including crisp and many-valued Kripke frames, and crisp and many-valued ...

The problem of minimizing finite fuzzy interpretations in fuzzy description logics (FDLs) is worth studying. For example, the structure of a fuzzy/weighted social network can be treated as a fuzzy interpretation in FDLs, where actors are ...

Adaptive-network-based fuzzy inference system (ANFIS) is a well-known neuro-fuzzy system, which is widely implemented in nonlinear system approximation, prediction, control, and pattern classification. However, either too many fuzzy sets or fuzzy ...

The Adaptive Neuro-Fuzzy Inference System (ANFIS) is a regression model that uses fuzzy logic and neural networks, making it suitable for modeling the uncertainty of regression problems. However, the non-robust loss function in ANFIS's hybrid ...

• Introduce a new version of the hybrid learning algorithm for Adaptive Neuro-Fuzzy Inference Systems.
• Emphasis on the significance of using different loss functions for parameter optimization.
• Improve hybrid learning robustness ...

The aim of this paper is to combine the time-frequency attributes of wavelets and neural network learning ability besides approximate reasoning features of type 2- fuzzy systems, and the advantages of online sequential extreme learning machine (...

In this paper, we construct uninorms on a bounded trellis based on t-(co)norms on a ∧ ( ∨ )-semi-trellis and closure (interior) operators. The key is how to ensure the monotonicity of the constructed binary operation, which is closely related to ...

Besides the mean, the median is the most widely used single-valued descriptor of data sets. It is well-known that the orness level of the median operator is 1/2. In this paper we provide approximations of the median operator under a given level ...

We introduce the notion of fuzzy degree of nondensifiability (FDND for short) as a non-negative real number that measures the Hausdorff distance between a bounded set of a fuzzy metric space and its closest Peano continuum. The FDND allows us to ...

This paper introduces some recent approaches to the fuzzy fractional Abel integral equations with respect to another function, which is called the fuzzy fractional Abel k−integral equations. The problem proposed here allows for the interpolation ...