A new combination approach based on improved evidence distance
This addresses an open issue in information fusion for applications like decision-making or sensor networks, but it appears incremental as it builds on existing distance measures and combination rules.
The paper tackled the problem of counter-intuitive results in Dempster-Shafer evidence theory when evidence is highly conflicting, by proposing a new method based on evidence and Hausdorff distances to compute weights and preprocess evidence, resulting in an efficient approach compared to existing methods.
Dempster-Shafer evidence theory is a powerful tool in information fusion. When the evidence are highly conflicting, the counter-intuitive results will be presented. To adress this open issue, a new method based on evidence distance of Jousselme and Hausdorff distance is proposed. Weight of each evidence can be computed, preprocess the original evidence to generate a new evidence. The Dempster's combination rule is used to combine the new evidence. Comparing with the existing methods, the new proposed method is efficient.