Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this iss...Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.展开更多
The threat sequencing of multiple unmanned combat air vehicles(UCAVs) is a multi-attribute decision-making(MADM)problem. In the threat sequencing process of multiple UCAVs,due to the strong confrontation and high dyna...The threat sequencing of multiple unmanned combat air vehicles(UCAVs) is a multi-attribute decision-making(MADM)problem. In the threat sequencing process of multiple UCAVs,due to the strong confrontation and high dynamics of the air combat environment, the weight coefficients of the threat indicators are usually time-varying. Moreover, the air combat data is difficult to be obtained accurately. In this study, a threat sequencing method of multiple UCAVs is proposed based on game theory by considering the incomplete information. Firstly, a zero-sum game model of decision maker( D) and nature(N)with fuzzy payoffs is established to obtain the uncertain parameters which are the weight coefficient parameters of the threat indicators and the interval parameters of the threat matrix. Then,the established zero-sum game with fuzzy payoffs is transformed into a zero-sum game with crisp payoffs(matrix game) to solve. Moreover, a decision rule is addressed for the threat sequencing problem of multiple UCAVs based on the obtained uncertain parameters. Finally, numerical simulation results are presented to show the effectiveness of the proposed approach.展开更多
Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its ...Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.展开更多
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...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。展开更多
以北京市四惠枢纽为研究对象,探索以数据驱动为导向满足乘客需求的枢纽动态导向标识方案评估及优化设计方法。首先,搭建KANO乘客需求模型,通过桌面实验,形成动态导向标识在内容、样式及空间位置上的优化设计方案,与四惠枢纽现有方案形...以北京市四惠枢纽为研究对象,探索以数据驱动为导向满足乘客需求的枢纽动态导向标识方案评估及优化设计方法。首先,搭建KANO乘客需求模型,通过桌面实验,形成动态导向标识在内容、样式及空间位置上的优化设计方案,与四惠枢纽现有方案形成对比。其次,基于寻路理论通过建筑信息建模(building information modeling,BIM)+虚拟现实(virtual reality,VR)仿真技术,实现人与枢纽的信息交互,提取新旧导向标识方案作用下乘客寻路过程的特征参数。最后,通过对寻路实验中主客观指标分析可知,被试在新版动态导向标识方案中寻路时间、犯错误点数及迷茫点数显著降低,且新版动态导向标识方案在内容、样式及空间位置上满意度均优于旧版。结果表明:研究搭建BIM+VR的虚拟仿真平台,形成以数据驱动为导向的枢纽动态导向标识方案综合评估及优化设计方法,为枢纽动态导向标识方案设计及合理应用提供技术与理论支撑。展开更多
基金supported by the National Natural Science Foundation of China(61903305,62073267)the Fundamental Research Funds for the Central Universities(HXGJXM202214).
文摘Dempster-Shafer evidence theory is broadly employed in the research of multi-source information fusion.Nevertheless,when fusing highly conflicting evidence it may pro-duce counterintuitive outcomes.To address this issue,a fusion approach based on a newly defined belief exponential diver-gence and Deng entropy is proposed.First,a belief exponential divergence is proposed as the conflict measurement between evidences.Then,the credibility of each evidence is calculated.Afterwards,the Deng entropy is used to calculate information volume to determine the uncertainty of evidence.Then,the weight of evidence is calculated by integrating the credibility and uncertainty of each evidence.Ultimately,initial evidences are amended and fused using Dempster’s rule of combination.The effectiveness of this approach in addressing the fusion of three typical conflict paradoxes is demonstrated by arithmetic exam-ples.Additionally,the proposed approach is applied to aerial tar-get recognition and iris dataset-based classification to validate its efficacy.Results indicate that the proposed approach can enhance the accuracy of target recognition and effectively address the issue of fusing conflicting evidences.
基金supported by the Major Projects for Science and Technology Innovation 2030 (2018AAA0100805)。
文摘The threat sequencing of multiple unmanned combat air vehicles(UCAVs) is a multi-attribute decision-making(MADM)problem. In the threat sequencing process of multiple UCAVs,due to the strong confrontation and high dynamics of the air combat environment, the weight coefficients of the threat indicators are usually time-varying. Moreover, the air combat data is difficult to be obtained accurately. In this study, a threat sequencing method of multiple UCAVs is proposed based on game theory by considering the incomplete information. Firstly, a zero-sum game model of decision maker( D) and nature(N)with fuzzy payoffs is established to obtain the uncertain parameters which are the weight coefficient parameters of the threat indicators and the interval parameters of the threat matrix. Then,the established zero-sum game with fuzzy payoffs is transformed into a zero-sum game with crisp payoffs(matrix game) to solve. Moreover, a decision rule is addressed for the threat sequencing problem of multiple UCAVs based on the obtained uncertain parameters. Finally, numerical simulation results are presented to show the effectiveness of the proposed approach.
文摘Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.
文摘多智能体信息融合(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。
文摘以北京市四惠枢纽为研究对象,探索以数据驱动为导向满足乘客需求的枢纽动态导向标识方案评估及优化设计方法。首先,搭建KANO乘客需求模型,通过桌面实验,形成动态导向标识在内容、样式及空间位置上的优化设计方案,与四惠枢纽现有方案形成对比。其次,基于寻路理论通过建筑信息建模(building information modeling,BIM)+虚拟现实(virtual reality,VR)仿真技术,实现人与枢纽的信息交互,提取新旧导向标识方案作用下乘客寻路过程的特征参数。最后,通过对寻路实验中主客观指标分析可知,被试在新版动态导向标识方案中寻路时间、犯错误点数及迷茫点数显著降低,且新版动态导向标识方案在内容、样式及空间位置上满意度均优于旧版。结果表明:研究搭建BIM+VR的虚拟仿真平台,形成以数据驱动为导向的枢纽动态导向标识方案综合评估及优化设计方法,为枢纽动态导向标识方案设计及合理应用提供技术与理论支撑。
