摘要
多智能体信息融合(multi-agent information fusion,MAIF)系统主要面向多个智能体之间的信息融合、调节、交流和矛盾处理。研究针对数据高度冲突条件下的D-S证据理论失效问题,提出一种将重构的基本概率分配和信念熵相结合的多智能体系统冲突数据融合方法。该方法使用重构的基本概率分配和信念熵修正证据的可靠性,获得更合理的证据,使用Dempster组合规则将证据进行融合得到结果,在2个实验中均得到了超过90%的置信度。实验表明了该方法的有效性,提高了MAIF系统辨识过程的精度。
The multi-agent information fusion(MAIF)system is smainly aimed at information fusion,regulation,communication,and conflict resolution among multiple agents.A multi-agent system conflict data fusion method combining reconstructed basic probability assignment and belief entropy is proposed to address the issue of D-S evidence theory failure under highly conflicting data conditions.This method uses reconstructed basic probability assignment and belief entropy to correct the reliability of evidence,obtaining more reasonable evidence.Then,the evidence is fused using the Dempster combination rule,and the results are obtained with a confidence level of over 90%in both 2 experiments.The experiment demonstrates the effectiveness of this method and improves the accuracy of the MAIF system identification process.
作者
王娜
刘静渝
李皓然
夏晓峰
WANG Na;LIU Jingyu;LI Haoran;XIA Xiaofeng(College of Mathematics and Computer Science,Hengshui University,Hengshui,Hebei 053000,P.R.China;School of Bigdata and Software Engineering,Chongqing University,Chongqing 400044,P.R.China;29th Research Institute of China Electronics Technology Group Corporation,Chengdu 610036,P.R.China)
出处
《重庆大学学报》
北大核心
2025年第2期22-34,共13页
Journal of Chongqing University
基金
成都市区域科技创新合作项目(2023-YF11-00018-HZ)
国家自然科学基金(62372075)。
关键词
基本概率分配
熵
D-S证据理论
多智能体
信息融合
basic probability assignment
entropy
D-S evidence theory
multi-agent
information fusion
作者简介
王娜(1981-),女,副教授,主要从事人工智能与数据分析方向研究,(E-mail)54775265@qq.com;通信作者:夏晓峰(1980-),男,副教授,硕士生导师,主要从事网络空间安全与人工智能方向研究,(E-mail)xiaxiaofeng@cqu.edu.cn。
