The principle of minimum specificity as a basis for evidential reasoning
Processing and Management of Uncertainty in Knowledge-Based Systems on Uncertainty in knowledge-based systems. International Conference on Information
International Journal of Approximate Reasoning
An aspect of discrepancy in the implementation of modus ponens in the presence of fuzzy quantities
International Journal of Approximate Reasoning
Fuzzy sets in approximate reasoning, part 1: inference with possibility distributions
Fuzzy Sets and Systems - Special memorial volume on foundations of fuzzy reasoning
A characterization of the Hamacher family of t-norms
Fuzzy Sets and Systems
Aggregation operators and fuzzy systems modeling
Fuzzy Sets and Systems
Study of some algebraical properties of adaptive combination rules
Fuzzy Sets and Systems
Fuzzy Measure Theory
Information combination operators for data fusion: a comparative review with classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An answer to an open problem on triangular norms
Information Sciences: an International Journal
Detection of defective sources in the setting of possibility theory
Fuzzy Sets and Systems
Cancellativity properties for t-norms and t-subnorms
Information Sciences: an International Journal
Fuzzy Aggregation with Artificial Color filters
Information Sciences: an International Journal
Possibilistic information fusion using maximal coherent subsets
IEEE Transactions on Fuzzy Systems
On prioritized weighted aggregation in multi-criteria decision making
Expert Systems with Applications: An International Journal
Score level fusion of multimodal biometrics using triangular norms
Pattern Recognition Letters
Prioritized multi-criteria decision making based on preference relations
Computers and Industrial Engineering
Statistical analysis of parametric t-norms
Information Sciences: an International Journal
Hi-index | 0.07 |
Combination of pieces of information issued from different sources plays a central role in several engineering as well as academic applications. The challenge that was usually addressed in these topics is how to deal with uncertainty and imperfection pervading the different sources of knowledge as well as with conflictual pieces of information. The theory of t-norms and t-conorms have been intensively investigated by many authors (see, for instance [E.P. Klement, R. Mesiar, E. Pap, Triangular Norms, Kluwer Academic Publisher, Dordrecht, 2000]) because of their appealing properties to model and manage the basic combination modes referring to a conjunctive and a disjunctive modes. Hamacher's family of t-norms [E.P. Klement, R. Mesiar, E. Pap, Triangular Norms, Kluwer Academic Publisher, 2000] offers a special interest because it supplies a wide class of t-norm operators ranging from the probabilistic product to the weakest t-norm. Dubois and Prade [Data Fusion in Robotics and Machine Intelligence, Academic Press, New York; Contr. Eng. Practice 2 (1994) 812] have proposed an interesting setting for dealing with conflict based on the adaptiveness property that allows a gradual moving from a conjunctive mode to a disjunctive mode as soon as the conflict increases. This paper attempts to capture the basic ideas of the adaptiveness in order to build new combination rules based on Hamacher's family. Particularly, certainty based qualification [R.R. Yager, Expert systems using fuzzy logic, in: R.R.Yager, L. Zadeh (Eds.), Intelligent Systems, Kluwer Academic Publisher, 1992, 27] will be reviewed and, accordingly, two families of rules will be put forward and compared to the adaptive rule of Dubois' and Prade's.