In this paper, the combination rules, such as the Dempster-Shafer's (D-S) combination rule, the Yager's combination rule, the Dubois and Prade's (D-P) combination rule, the DSm's combination rule and the disjunctive combination rule, are applied to the situation assessment and target identification problems. Given two independent sources of information with different resolutions, the results from each combination rule of evidence are analyzed. It is observed from these results that the DSm's rule is the fastest in arriving at a decision compared to the other three rules, while the disjunctive combination rule is the slowest. The Yager's rule yields the same identification results for the situation assessment as the Dubois and Prade's rule. Moreover, the decision-making of the D-S' rule is faster than that of the Yager's as well as of the Dubois and Prade's rules, however, slower than that of the DSm's rule
KEYWORDS: Probability theory, Sun, Beryllium, Information security, Electronics, Aluminum, Information fusion, Target recognition, Associative arrays, Data fusion
In this paper, the conjunctive and disjunctive combination rules of evidence, namely, the Dempster-Shafer' s (D-S) combination rule, the Yager's combination rule, the Dubois and Prade's (D-P) combination rule, the DSm's combination rule and the disjunctive combination rule, are studied for the two independent sources of information.
The properties of each combination rule of evidence are discussed in detail, such as the role of evidence of each source of information in the combination judgment, the comparison of the combination judgment belief and ignorance of each combination rule, the treatment of conflict judgments given by the two sources of information, and the applications of combination rules. Zadeh' s example is included in the paper to evaluate the performance as
well as efficiency of each combination rule of evidence for the conflict judgments given by the two sources of information.
Based on a multi-valued mapping from a probability space (X,(Omega) ,Rmu) to space S, a probability measure over a class 2s of subsets of S is defined. Then using the product combination rule of multiple information sources, the Dempster-Shafer combination rule is derived. The investigation of the two rules indicates that the Dempster rule and the Dempster-Shafer combination rule are for different spaces. Some problems of the Dempster-Shafer combination rule are interpreted via the product combination rule that is used for multiple independent information sources. A technique to improve the method is proposed. Finally, an error in multi-valued mappings in [20] is pointed out and proved.
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