On the Dempster-Shafer framework and new combination rules
Information Sciences: an International Journal
The Combination of Evidence in the Transferable Belief Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
A qualitative discriminant process for scoring and ranking in group support systems
Information Processing and Management: an International Journal
Combining belief functions when evidence conflicts
Decision Support Systems
The consensus operator for combining beliefs
Artificial Intelligence
Representation of Qualitative User Preference by Quantitative Belief Functions
IEEE Transactions on Knowledge and Data Engineering
Non-additive measures by interval probability functions
Information Sciences—Informatics and Computer Science: An International Journal
Combining belief functions based on distance of evidence
Decision Support Systems
On the combination and normalization of interval-valued belief structures
Information Sciences: an International Journal
Analyzing the combination of conflicting belief functions
Information Fusion
Reasoning with imprecise belief structures
International Journal of Approximate Reasoning
Expert Systems with Applications: An International Journal
Maximal confidence intervals of the interval-valued belief structure and applications
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Evidential calibration process of multi-agent based system: An application to forensic entomology
Expert Systems with Applications: An International Journal
The conjunctive combination of interval-valued belief structures from dependent sources
International Journal of Approximate Reasoning
| Hi-index | 12.06 |
It has become a noticeable topic on how to construct belief functions from the quantitative and qualitative opinions of one expert. The existing methods proposed in the literature addressing the topic, however, have paid little attention to the bounded rationality (BR) of the expert. This paper introduces a confidence belief function (BF) qualitatively and quantitatively under the assumption of BR, generated from a set of BFs sampled from the expert by interacting with a number of reliable information providers in a valid time interval. Besides, a procedure for quantitatively producing a confidence BF is presented, which is based on a statistical method mainly involving three steps, dividing the set of BFs into a number of non-conflicting or consistent subsets, forming the confidence interval-valued belief structures (IBSs) of the subsets, and integrating the IBSs into the confidence IBS of the set. A numerical example about a manager in a telecommunications company deciding whether to upgrade a business campaign or not is given to show the procedure for generating a confidence BF. Since the method of generating a confidence BF is on the power set of a frame of discernment, its scalability is also discussed.