Read Entropy's recent Article "Some Theoretical Foundations of Bare-Simulation Optimization of Some Directed Distances between Fuzzy Sets Respective

Authors: Michel Broniatowski and Wolfgang Stummer

Read full article at: https://www.mdpi.com/1099-4300/26/4/312

Abstract: It is well known that in information theory—as well as in the adjacent fields of statistics, machine learning and artificial intelligence—it is essential to quantify the dissimilarity between objects of uncertain/imprecise/inexact/vague information; correspondingly, constrained optimization is of great importance, too. In view of this, we define the dissimilarity-measure-natured?generalized φ–divergences?between fuzzy sets,???–rung orthopair fuzzy sets, extended representation type???–rung orthopair fuzzy sets as well as between those fuzzy set types and vectors. For those, we present how to tackle corresponding constrained minimization problems by appropriately applying our recently developed dimension-free?bare (pure) simulation method. An analogous program is carried out by defining and optimizing?generalized φ–divergences?between (rescaled) basic belief assignments as well as between (rescaled) basic belief assignments and vectors.

Keywords: generalized φ–divergences; fuzzy sets; basic belief assignments