摘要
为了有效融合高度冲突的证据,以Murphy方法和邓勇加权平均法为基础,提出了一种新的基于加权证据距离的证据组合方法。用Murphy方法确定各证据体的权重,采用修正的City Block距离加权平均求证据间的两两距离,进而获取各证据被其他所有证据支持的程度,归一化各证据的总支持度作为该证据的权重,对多源证据加权平均后再利用Dempster组合规则实现信息融合。实验结果表明,该方法能够更加有效快速地识别出目标,拥有更快的收敛速度。
In order to efficiently combine highly conflict evidence, this paper proposes a new combination method based on the weighted distance of evidence by using Murphy’s method and Deng’s weighted averaging method. The weight of each body of evidence is determined by using Murphy’s method. The weighted distance between every two evidences is calculated under the modified City Block distance norm, so the support degree of each evidence supported by other evi-dences can be obtained. After normalizing the general support degree of each evidence as the weight of each evidence, the information fusion process under the Dempster combination rule can be realized. Simulation results show that the new method converges at a faster rate and can recognise the target more effectively and fleetly.
出处
《计算机工程与应用》
CSCD
2014年第3期103-107,共5页
Computer Engineering and Applications
基金
"十一五"国家部委预研基金项目
