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
Robust reasoning: integrating rule-based and similarity-based reasoning
Artificial Intelligence
Combining belief functions when evidence conflicts
Decision Support Systems
Modeling vague beliefs using fuzzy-valued belief structures
Fuzzy Sets and Systems - Special issue on fuzzy numbers and uncertainty
Current Approaches to Handling Imperfect Information in Data and Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
On the combination and normalization of interval-valued belief structures
Information Sciences: an International Journal
Analyzing the combination of conflicting belief functions
Information Fusion
Information Sciences: an International Journal
A DS-AHP approach for multi-attribute decision making problem with incomplete information
Expert Systems with Applications: An International Journal
A new method for solving interval and fuzzy equations: Linear case
Information Sciences: an International Journal
Reasoning with imprecise belief structures
International Journal of Approximate Reasoning
Fuzzy solution of interval linear equations
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
A new approach to the rule-base evidential reasoning: Stock trading expert system application
Expert Systems with Applications: An International Journal
A fuzzy-evidential hybrid inference engine for coronary heart disease risk assessment
Expert Systems with Applications: An International Journal
The normalization of the Dempster's rule of combination
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Combining uncertainty and imprecision in models of medical diagnosis
Information Sciences: an International Journal
On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Belief rule-base inference methodology using the evidential reasoning Approach-RIMER
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Optimization Models for Training Belief-Rule-Based Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Hi-index | 12.05 |
A new framework for rule-base evidential reasoning in the interval setting is presented. While developing this framework, two collateral problems such as combining and normalizing interval-valued belief structures from different sources and comparing resulting belief intervals, the bounds of which are intervals, arise. The first problem is solved with the use of the so-called ''interval extended zero'' method. It is shown that interval valued results of the proposed approach to combining and normalizing interval-valued belief structures are enclosed in those obtained by known methods and possess three desirable intuitively obvious properties of normalization procedure defined in the paper. The second problem is solved using the method for interval comparison based on the Demposter-Shafer theory providing the interval valued results of comparison. The advantages of the proposed framework for rule-base evidential reasoning in the interval setting are demonstrated using the developed expert system for diagnosing type 2 diabetes.