Uncertainty computations in model-based diagnostics

摘要

The authors briefly describe the computational methods used in uncertainty data gathering (modified fuzzy logic), evidence accumulation (modified Dempster-Shafer), and termination of the evidence-gathering process (backpropagation neural network) as they are implemented in the POINTER system. An example demonstrates the proposed approach.