Evidence theory is an important method for uncertainty reasoning. Because evidence theory can well process uncertain information, imprecise information, fuzzy information, and information without prior knowledge, it is wildly used in information fusion, expert system, fuzzy recognition, and intelligent decision system. This paper depend on original evidence theory fusion algorithm, put forward ...

Decision Making is a core area in different research fields related to human beings' intelligent activities; such activities involve different types of uncertainties depending on its nature. Therefore, different methods, models and formalisms have been investigated and applied to a wide range of decision making problems under uncertainty. This special issue is devoted to information fusion mode...

the current study set to extend a new vikor method as a compromise ranking approach to solve multiple criteria decision-making (mcdm) problems through intuitionistic fuzzy analysis. using compromise method in mcdm problems contributes to the selection of an alternative as close as possible to the positive ideal solution and far away from the negative ideal solution, concurrently. using atanasso...

The present report further investigates the multi-criteria decision making tool named Fuzzy Compromise Programming. Comparison of different fuzzy set ranking methods (required for processing fuzzy information) is performed. A complete sensitivity analysis concerning decision maker’s risk preferences was carried out for three water resources systems, and compromise solutions identified. Then, a ...

Decision tree induction is one of common approaches for extracting knowledge from a sets of feature-based examples. In real world, many data occurred in a fuzzy and uncertain form. The decision tree must able to deal with such fuzzy data. This paper presents a tree construction procedure to build a fuzzy decision tree from a collection of fuzzy data by integrating fuzzy set theory and entropy. ...