Part 7: DecisionsInternational audienceIn this study, we discuss the use of Dempster-Shafer theory as a well-rounded algorithmic vehicle in the construction of fuzzy decision rules. The concept of fuzzy granulation realized via fuzzy clustering is aimed at the discretization of continuous attributes. Detailed experimental studies are presented concerning well-known medical data sets available on the Web
We develop a new approach for decision making with Dempster-Shafer (D-S) theory of evidence. We focu...
Part 5: Modelling and OptimizationInternational audienceThe article presents an application of fuzzy...
This book contains the successful invited submissions to a Special Issue of Symmetry in the subject ...
This research aims to combine the mathematical theory of evidence with the rule based logics to refi...
Dempster-Shafer evidence theory (D-S) is an effective instrument for merging the collected pieces of...
In this paper, an extended ranking method for fuzzy numbers, which is a synthesis of fuzzy targets a...
We study the problem of decision making with Dempster-Shafer belief structure. We analyze the previo...
The paper presents a study on data-driven diagnostic rules, which are easy to interpret by human exp...
We develop a new approach for decision making with Dempster-Shafer (D-S) theory of evidence. We focu...
Two approaches have traditionally been identified for developing artificial intelligence systems sup...
The objective of this paper is to describe the potential offered by the Dempster–Shafer theory (DST)...
Data mining and knowledge discovery is described from pattern recognition point of view along with t...
Fuzzy logic provides a mathematical formalism for a unified treatment of vagueness and imprecision t...
Abstract Forest management decisions often must be made using sparse data and expert judgment. The r...
Expert systems are usually used only to help get the results of a diagnosis faster. In the expert sy...
We develop a new approach for decision making with Dempster-Shafer (D-S) theory of evidence. We focu...
Part 5: Modelling and OptimizationInternational audienceThe article presents an application of fuzzy...
This book contains the successful invited submissions to a Special Issue of Symmetry in the subject ...
This research aims to combine the mathematical theory of evidence with the rule based logics to refi...
Dempster-Shafer evidence theory (D-S) is an effective instrument for merging the collected pieces of...
In this paper, an extended ranking method for fuzzy numbers, which is a synthesis of fuzzy targets a...
We study the problem of decision making with Dempster-Shafer belief structure. We analyze the previo...
The paper presents a study on data-driven diagnostic rules, which are easy to interpret by human exp...
We develop a new approach for decision making with Dempster-Shafer (D-S) theory of evidence. We focu...
Two approaches have traditionally been identified for developing artificial intelligence systems sup...
The objective of this paper is to describe the potential offered by the Dempster–Shafer theory (DST)...
Data mining and knowledge discovery is described from pattern recognition point of view along with t...
Fuzzy logic provides a mathematical formalism for a unified treatment of vagueness and imprecision t...
Abstract Forest management decisions often must be made using sparse data and expert judgment. The r...
Expert systems are usually used only to help get the results of a diagnosis faster. In the expert sy...
We develop a new approach for decision making with Dempster-Shafer (D-S) theory of evidence. We focu...
Part 5: Modelling and OptimizationInternational audienceThe article presents an application of fuzzy...
This book contains the successful invited submissions to a Special Issue of Symmetry in the subject ...