Vague Sets Based Evidence Combinational Rule With Generalized Belief Function

Abstract

In this paper, a new vague evidence theory is proposed to expand the conventional evidence theory. First, the concept of vague evidence theory is introduced. Based on the features of vague sets, a belief function is formulated, and its characteristics is analyzed and proved mathematically. After that, based on the degree of similarity in vague sets, the relative contribution to the combined vague sets is obtained, and a vague sets based combinational rule is formulated. Finally, experiments are conducted to demonstrate the effectiveness of the proposed vague evidence theory. The proposed vague evidence theory based method is capable of representing and processing problems with vagueness, uncertainties and imprecision.