Khái niệm cốt lõi
The author introduces the Evidence Pattern Reasoning Model (EPRM) as an improvement over the Transferable Belief Model (TBM) to accommodate preferences in decision making. The Random Graph Set (RGS) is proposed to model complex relationships effectively.
Tóm tắt
The content discusses the application of EPRM and RGS in decision-making processes, focusing on aircraft velocity ranking experiments. It explains the theoretical background, algorithms, and simulation results with detailed examples and statistical analysis.
Evidence theory is applied in decision making.
EPRM improves upon TBM by accommodating preferences.
RGS models complex relationships effectively.
Aircraft velocity sorting experiment explained.
Detailed algorithms for BPA, PO, pattern fusion, and decision making provided.
Simulation results analyzed with heat maps for MVD and CRD.
Thống kê
The implementation of EPRM optimized 18.17% of cases compared to Mean Velocity Decision.
Sensor 1: Aircraft 1 mean velocity - 0.418; Aircraft 2 mean velocity - 0.423; Aircraft 3 mean velocity - 0.516.
Sensor 2: Aircraft 1 mean velocity - 0.44; Aircraft 2 mean velocity - 0.453; Aircraft 3 mean velocity - 0.47.
Sensor 3: Aircraft 1 mean velocity - 0.423; Aircraft 2 mean velocity - 0.436; Aircraft 3 mean velocity - 0.504.
Sensor 4: Aircraft 1 mean velocity - 0.411; Aircraft...
Trích dẫn
"The focal element representation needs improvement."
"EPRM provides a unified solution for evidence-based decision making."