Approach of conflict evidence judgment and combination based on clustering analysis

D-S evidence theory cannot combine highly conflict evidence and brings counterintuitive results. In order to solve this issue, a new conflict evidence combination approach was proposed from clustering analysis. Firstly, cosine similarity space in which evidence was regarded as space vecter was built up, and cosine between evidence vectors was calculated to define conflict evidence detection coefficient. Based on the space and coefficient, conflict evidence criterion was presented to judge the conflict evidence, and the evidence was classified into similar evidence and conflict evidecne. Secondly, conflict proportion coefficient was introduced to decide the modified method in which conflict evidence was modified by use of the absolute similarity and all the evidence was modified by use of the relative similarity. Finally, the modified evidence was put into D-S combination formula to combine. Application examples prove that this new method can judge conflict evidence and combine them effectively, and processes good classification precision, convergence speed and stability.