[目的/意义]系统审视并分析国外冲突性健康信息研究的现状、热点以及前沿,以全面把握该领域的发展情况,为未来研究提供有益的参考和支持。[方法/过程]在Web of Science和Elsevier ScienceDirect两个外文数据库中检索冲突性健康信息的研...[目的/意义]系统审视并分析国外冲突性健康信息研究的现状、热点以及前沿,以全面把握该领域的发展情况,为未来研究提供有益的参考和支持。[方法/过程]在Web of Science和Elsevier ScienceDirect两个外文数据库中检索冲突性健康信息的研究文献,利用VOSviewer可视化工具分析文献的发文趋势以及研究热点和前沿,并对这些分析结果进行详细的阐释和说明。[结果/结论]国外冲突性健康信息研究正处于高速发展阶段,研究热点包括:冲突性健康信息产生原因和来源研究、冲突性健康信息对公众健康认知和行为的影响研究、冲突性健康信息下的公众健康决策研究以及冲突性健康信息应对和治理研究。研究前沿涵盖了不确定性视角下的冲突性健康信息、冲突性健康信息的延滞效应以及跨学科理论的冲突性健康信息研究。展开更多
Based on the framework of evidence theory, data fusion aims at obtaining a single Basic Probability Assignment (BPA) function by combining several belief functions from distinct information sources. Dempster’s rule o...Based on the framework of evidence theory, data fusion aims at obtaining a single Basic Probability Assignment (BPA) function by combining several belief functions from distinct information sources. Dempster’s rule of combination is the most popular rule of combinations, but it is a poor solution for the management of the conflict between various information sources at the normalization step. Even when it faces high conflict information, the classical Dempster-Shafer’s (D-S) evidence theory can involve counter-intuitive results. This paper presents a modified averaging method to combine conflicting evidence based on the distance of evidences; and also gives the weighted average of the evidence in the system. Numerical examples showed that the proposed method can realize the modification ideas and also will provide reasonable results with good convergence efficiency.展开更多
文摘[目的/意义]系统审视并分析国外冲突性健康信息研究的现状、热点以及前沿,以全面把握该领域的发展情况,为未来研究提供有益的参考和支持。[方法/过程]在Web of Science和Elsevier ScienceDirect两个外文数据库中检索冲突性健康信息的研究文献,利用VOSviewer可视化工具分析文献的发文趋势以及研究热点和前沿,并对这些分析结果进行详细的阐释和说明。[结果/结论]国外冲突性健康信息研究正处于高速发展阶段,研究热点包括:冲突性健康信息产生原因和来源研究、冲突性健康信息对公众健康认知和行为的影响研究、冲突性健康信息下的公众健康决策研究以及冲突性健康信息应对和治理研究。研究前沿涵盖了不确定性视角下的冲突性健康信息、冲突性健康信息的延滞效应以及跨学科理论的冲突性健康信息研究。
基金Project (No. 51476040103JW13) supported by the National DefenseKey Laboratory of Target and Environment Feature of China
文摘Based on the framework of evidence theory, data fusion aims at obtaining a single Basic Probability Assignment (BPA) function by combining several belief functions from distinct information sources. Dempster’s rule of combination is the most popular rule of combinations, but it is a poor solution for the management of the conflict between various information sources at the normalization step. Even when it faces high conflict information, the classical Dempster-Shafer’s (D-S) evidence theory can involve counter-intuitive results. This paper presents a modified averaging method to combine conflicting evidence based on the distance of evidences; and also gives the weighted average of the evidence in the system. Numerical examples showed that the proposed method can realize the modification ideas and also will provide reasonable results with good convergence efficiency.