A Situation Assessment Method in Conditional Evidential Networks based on DSm-PCR5

Aiming to solving the problem that the evidence information based on Dezert-Smarandache (DSm) model cannot be effectively conditionally reasoned in multi-source heterogeneous network which leads to the low rate of situation assessment, a situation assessment method in Conditional Evidential Network based on DSm-Proportional Conflict Redistribution No.5 (PCR5) is proposed. First, the conditional reasoning formula in Conditional Evidential Network based on DSm model is given. Then, the Disjunctive Rule of Combination(DRC) based on DSm-PCR5 is proposed and the Generalized Bayesian Theorem (GBT) for multiple intersection sets of focal elements can be obtained in the premise that the conditional mass assignments functions of focal elements in refinement of hyper-power set is known. Finally, through the simulation experiments results of situation assessment, the effectiveness of the proposed method is verified.