GENERALIZATION OF THE CLASSIC COMBINATION RULES TO DSm HYPER-POWER SETS
نویسندگان
چکیده
In this article, the author generalizes Dempster’s rule, Yager’s rule, and Dubois-Prade’s rule for belief functions combination in order to be applicable to hyper-power sets according to the Dezert-Smarandache (DSm) Theory. A comparison of the rules with the DSm rule of combination is further presented.
منابع مشابه
A GENERALIZATION OF THE CLASSIC COMBINATION RULES TO DSm HYPER-POWER SETS
Dempster’s rule, Yager’s rule and Dubois-Prade’s rule for belief functions combination are generalized to be applicable to hyper-power sets according to the DSm theory. A comparison of the rules with DSm rule of combination is presented.
متن کاملClassical Belief Conditioning and its Generalization to DSm Theory
Brief introductions to both Dempster-Shafer and DSm theories are presented. Classical belief conditioning is recalled and generalized to DSm hyper-power sets. Relation of generalization of classic conditioning rules to belief conditioning defined in DSmT is discussed. c ©2008 World Academic Press, UK. All rights reserved.
متن کاملA Comparison of the Generalized minC Combination and the Hybrid DSm Combination Rules
A generalization of the minC combination to DSm hyper-power sets is presented. Both the special formulas for static fusion or dynamic fusion without non-existential constraints and the quite general formulas for dynamic fusion with non-existential constraints are included. Examples of the minC combination on several different hybrid DSm models are presented. A comparison of the generalized minC...
متن کاملGeneralized to DSm Hyper - power Sets and their Comparison with the Hybrid DSm Rule
Dempster’s rule, non-normalized conjunctive rule, Yager’s rule and Dubois-Prade’s rule for belief functions combination are generalized to be applicable to hyper-power sets according to the DSm theory. A comparison of the rules with DSm rule of combination is presented. A series of examples is included.
متن کاملHyper-rectangle-based Discriminative Data Generalization and Applications in Data Mining
The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuitions and insights. Axis-parallel hyper-rectangles provide interpretable generalizations for multi-dimensional data points with numerical attributes. In this dissertation, we study the fundamental problem of rectangle-ba...
متن کامل