1) combination of weighted evidence
加权证据组合
2) weighted evidence
加权证据
1.
The problem of multi-sensor target identification is researched,a new approach to weighted evidence data fusion is proposed.
给出了证据理论的基本概念、组合规则、加权证据组合及决策规则,同时给出简单的多传感器信息融合模型。
3) weighted weights of evidence
加权证据权
1.
This paper proposes two kinds of new models of weight of evidence:weighted weights of evidence and stepwise weights of evidence to reduce the influence of correlation among evidence layers when hypothesis of conditional independence is not held.
为了消除和减弱当证据层不满足条件独立性假设时对预测结果产生的影响,提出了逐步证据权模型和加权证据权模型。
4) evidence combination
证据组合
1.
Dynamic evidence combination rules based on time conversion;
基于时间换算的动态证据组合规则
2.
On the basis of analyzing and comparing some typical researches,a new approximation algorithm was proposed,which could not only accelerate the speed of evidence combination,but also overcome a defect of sacrifice precision for speed in old approximation algorithms and ensure accuracy of fusion results.
提出了一种新的D-S证据理论近似快速算法,它利用证据平均能量函数选择参加融合的焦元,并将被抛弃焦元的mass值分配在参加融合的焦元中,仿真结果证明该方法不但能够加快证据组合的运算速度,而且还克服以往近似算法中为了快速而牺牲精度的缺点,保证了融合结果的准确性。
6) Dempster evidence combination
Dempster证据组合
1.
Based on Dempster evidence combination, a method developed to weaken the influence of false evidence is proposed.
基于Dempster证据组合 ,提出了一种针对已经参与融合的伪证据 ,通过对附加证据的融合 ,减弱其影响的一种方法。
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