D-S Evidence Theory Belief Calculation

This text discusses how to calculate belief in D-S evidence theory. For those unfamiliar with D-S evidence, this may represent a relatively novel concept. Therefore, before performing belief calculations, we must first understand the definition and applications of D-S evidence. D-S evidence theory is an uncertainty reasoning method that enables inference under conditions of incomplete information. The key aspect of this approach lies in combining evidence rather than using traditional logical reasoning. Consequently, we need to determine the weight of each evidence source and combine them to derive final belief values. In practical implementation, this typically involves creating mass functions for each evidence source and applying Dempster's rule of combination - often implemented through matrix operations or iterative combination algorithms. The combination rule can be expressed mathematically as: m₁₂(A) = K⁻¹∑(m₁(B)×m₂(C)) where B∩C=A and K represents the conflict coefficient. In this article, we will detail this combination process and provide practical examples with code snippets demonstrating how to implement mass function normalization and evidence combination using probability assignment matrices, helping readers better understand D-S evidence theory.