关键词: 扩展置信规则库（EBRB）, 证据推理（ER）, BK树, 优化框架

Abstract: To the problem of undesirable inference efficiency in extended belief rule base (EBRB) with large number of rules, this paper introduces BK-tree data structure and proposes a structure optimization framework based on BK-tree. Firstly, the index with tree structure of EBRB is made by the metric distance between the belief rules in the metric space. By setting the threshold, reducing the number of search rules and activating the key rules, the reasoning efficiency of the EBRB system is improved. Finally, simulation experiments on a nonlinear function, a practical pipeline leak detection problem and multiple classification data sets are conducted to validate the performance of the optimization framework combined with EBRB system. The experimental results show the proposed method can be used to optimize the reasoning efficiency and decision accuracy of the EBRB system.

Key words: extended belief rule base (EBRB), evidential reasoning (ER), BK-tree, optimization framework