A New Solution Based on “Conjunctive & Disjunctive Pooling” and Pignistic Probability Transforms According to the Evidence Conflict Problems in D-S Theory of Evidence
Li Jin · 2007
According to the defect that in the D-S Theory of Evidence, the evidence combination rules can’t work correctly facing high conflicting evidences, a new solution based on “conjunctive disjunctive pooling” and Pignistic probability transforms is introduced. The solution supposes that at least one evidence is true among all the given evidences. When evidence A and B are consistent which means both the evidences are true, the beliefs of evidences will focus on their conjunctive pooling. On the other hand, when evidence A and B are inconsistent which means can’t judge which evidence is true, the beliefs of evidences will focus on their disjunctive pooling. In object recognition systems, owing to the request of single final output, a pignistic probability transform is used to reassign the basic probability assignments of multi-element propositions to each element thus the final output is the one with the highest belief.The experiment results show that the solution can get best performance evaluation. Finally, the sequence of evidence fusion has no effect on fusion results so the solution can be programmed easily.