A Direct Trust Aggregation Algorithm Based on the Minimum Variance Time Sequence Weight

Direct trust relationship is the foundation of research on the indirect recommendation trust between agents and the global trust degree. In view of the lack of analysis and attention on the direct trust in the current research of dynamic trust relationship, this paper proposes a minimum variance time sequence weight based direct trust aggregation algorithm which is constrained by the fuzzy integration operator orness measurement level. The algorithm introduces the concept of agent reputation, elaborates the evolution process and the law of the trust in the process of direct interaction, and further characterizes the complexity and stability of direct trust relationship. The simulation experimental results show that the model has a good dynamic adaptability and scalability compared with the conventional model.