基于团树传播的证据网络推理算法
发布时间：2018-08-22 18:00
【摘要】：将团树传播算法应用于证据网络中,解决复杂的多连通知识网络结构下的信度推理问题.将复杂多连通网络构造成一棵团树,并将联合信度作为团节点的参数实现复杂多连通网络结构上的证据网络信度推理.在进行联合信度函数信息融合的过程中,通过引入两种新的交并运算实现对DSm T组合规则的改进,减少不确定性.最后通过实例验证了所提出方法的可行性.
[Abstract]:The cluster tree propagation algorithm is applied to the evidence network to solve the reliability reasoning problem under the complex multi-connected knowledge network structure. The complex multi-connected network is constructed into a cluster tree, and the joint reliability is taken as the parameter of the cluster node to realize the reliability reasoning of the evidential network on the complex multi-connected network structure. In the process of information fusion of joint reliability function, two new intersection and union operations are introduced to improve DSm T combination rules and reduce uncertainty. Finally, the feasibility of the proposed method is verified by an example.
【作者单位】： 江西师范大学数学与信息科学学院;
【基金】：江西省自然科学基金项目(20151BAB207030) 江西省教育厅科技项目(GJJ14244)
【分类号】：TP202
，
本文编号：2197878
[Abstract]:The cluster tree propagation algorithm is applied to the evidence network to solve the reliability reasoning problem under the complex multi-connected knowledge network structure. The complex multi-connected network is constructed into a cluster tree, and the joint reliability is taken as the parameter of the cluster node to realize the reliability reasoning of the evidential network on the complex multi-connected network structure. In the process of information fusion of joint reliability function, two new intersection and union operations are introduced to improve DSm T combination rules and reduce uncertainty. Finally, the feasibility of the proposed method is verified by an example.
【作者单位】： 江西师范大学数学与信息科学学院;
【基金】：江西省自然科学基金项目(20151BAB207030) 江西省教育厅科技项目(GJJ14244)
【分类号】：TP202
，
本文编号：2197878
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