In real life, lots of information merges from time to time. To appropriately describe the actual situations, lots of theories have been proposed. Among them, Dempster-Shafer evidence theory is a very useful tool in managing uncertain information. To better adapt to complex situations of open world, a generalized evidence theory is designed. However, everything occurs in sequence and owns some underlying relationships with each other. In order to further embody the details of information and better conforms to situations of real world, a Markov model is introduced into the generalized evidence theory which helps extract complete information volume from evidence provided. Besides, some numerical examples is offered to verify the correctness and rationality of the proposed method.
翻译:在现实生活中,许多信息不时地相互融合,为了适当描述实际情况,提出了许多理论,其中包括:Dempster-Shafer证据理论是管理不确定信息的一个非常有用的工具;为了更好地适应开放世界的复杂情况,设计了一个普遍的证据理论;然而,每件事都按顺序发生,彼此之间有一些内在的关系;为了进一步体现信息的细节,更好地与现实世界的情况保持一致,在一般证据理论中引入了Markov模式,这有助于从提供的证据中提取完整的信息量;此外,还提供了一些数字例子,以核实拟议方法的正确性和合理性。