Dempster-Shafer (DS) theory of evidence has been widely used in many data fusion ap- plication systems. However, how to determine basic probability assignment, which is the main and the first step in evidence theory, ...Dempster-Shafer (DS) theory of evidence has been widely used in many data fusion ap- plication systems. However, how to determine basic probability assignment, which is the main and the first step in evidence theory, is still an open issue. In this paper, a new method to obtain Basic Probability Assignment (BPA) is proposed based on the similarity measure between generalized fuzzy numbers. In the proposed method, species model can be constructed by determination of the min, average and max value to construct a fuzzy number. Then, a new Radius Of Gravity (ROG) method to determine the similarity measure between generalized fuzzy numbers is used to calculate the BPA functions of each instance. Finally, the efficiency of the proposed method is illustrated by the classi- fication of Iris data.展开更多
How to efficiently measure the distance between two basic probability assignments（BPAs） is an open issue. In this paper, a new method to measure the distance between two BPAs is proposed, based on two existing measu...How to efficiently measure the distance between two basic probability assignments（BPAs） is an open issue. In this paper, a new method to measure the distance between two BPAs is proposed, based on two existing measures of evidence distance. The new proposed method is comprehensive and generalized. Numerical examples are used to illustrate the effectiveness of the proposed method.展开更多
针对雷达辐射源参数的不确定性,研究区间类型的雷达辐射源参数识别,构造区间参数的雷达辐射源数据库。首先,利用区间数距离形成区间相似度并基于此构造一种切合实际的基本概率赋值(basic probability assignment,BPA)。再将其与证据理...针对雷达辐射源参数的不确定性,研究区间类型的雷达辐射源参数识别,构造区间参数的雷达辐射源数据库。首先,利用区间数距离形成区间相似度并基于此构造一种切合实际的基本概率赋值(basic probability assignment,BPA)。再将其与证据理论结合形成辐射源识别的信度区间,利用证据组合规则对信度区间进行区间重组。最后进行自适应判决识别,得到识别结果。仿真结果表明,区间证据理论方法能够较好的处理区间类型以及区间值和标量值混合类型的辐射源参数,得到满意的识别结果,具有一定实际意义。展开更多
基本概率指派(Basic probability assignment,BPA)生成是应用D-S证据理论的关键环节和第一步,而如何生成BPA仍然是一个有待解决的问题。本文提出一种基于云模型的BPA生成方法,首先,采用逆向云发生器生成每类样本在某属性下的正态云模型...基本概率指派(Basic probability assignment,BPA)生成是应用D-S证据理论的关键环节和第一步,而如何生成BPA仍然是一个有待解决的问题。本文提出一种基于云模型的BPA生成方法,首先,采用逆向云发生器生成每类样本在某属性下的正态云模型。其次,利用前件云发生器得到待测样本在该属性下对每类样本的确定度期望。再次,给出一种正态云模型交叠度计算方法,用确定度最大类的正态云模型与其他种类的最大交叠度作为对全集的信任度。最后,对确定度进行归一化得到待测样本的BPA。实验结果验证了该方法的有效性,此外,在样本数据较少情况下也能有效生成BPA。展开更多
基金Supported by National High Technology Project (863)(No. 2006AA02Z320)the National Natural Science Founda-tion of China (No.30700154, No.60874105)+1 种基金Zhejiang Natural Science Foundation (No.Y107458, RY1080422)the School Youth Found of Shanghai Jiaotong University
文摘Dempster-Shafer (DS) theory of evidence has been widely used in many data fusion ap- plication systems. However, how to determine basic probability assignment, which is the main and the first step in evidence theory, is still an open issue. In this paper, a new method to obtain Basic Probability Assignment (BPA) is proposed based on the similarity measure between generalized fuzzy numbers. In the proposed method, species model can be constructed by determination of the min, average and max value to construct a fuzzy number. Then, a new Radius Of Gravity (ROG) method to determine the similarity measure between generalized fuzzy numbers is used to calculate the BPA functions of each instance. Finally, the efficiency of the proposed method is illustrated by the classi- fication of Iris data.
基金supported by the National High Technology Research and Development Program of China(863 Program)(2013AA013801)the National Natural Science Foundation of China(61174022+4 种基金61573290)the open funding project of State Key Laboratory of Virtual Reality Technology and Systemsthe Beihang University(BUAA-VR-14KF-02)the General Research Program of Natural Science of Sichuan Provincial Department of Education(14ZB0322)the Self-financing Program of State Ethnic Affairs Commission of China(14SCZ014)
文摘How to efficiently measure the distance between two basic probability assignments（BPAs） is an open issue. In this paper, a new method to measure the distance between two BPAs is proposed, based on two existing measures of evidence distance. The new proposed method is comprehensive and generalized. Numerical examples are used to illustrate the effectiveness of the proposed method.
文摘针对雷达辐射源参数的不确定性,研究区间类型的雷达辐射源参数识别,构造区间参数的雷达辐射源数据库。首先,利用区间数距离形成区间相似度并基于此构造一种切合实际的基本概率赋值(basic probability assignment,BPA)。再将其与证据理论结合形成辐射源识别的信度区间,利用证据组合规则对信度区间进行区间重组。最后进行自适应判决识别,得到识别结果。仿真结果表明,区间证据理论方法能够较好的处理区间类型以及区间值和标量值混合类型的辐射源参数,得到满意的识别结果,具有一定实际意义。
文摘基本概率指派(Basic probability assignment,BPA)生成是应用D-S证据理论的关键环节和第一步,而如何生成BPA仍然是一个有待解决的问题。本文提出一种基于云模型的BPA生成方法,首先,采用逆向云发生器生成每类样本在某属性下的正态云模型。其次,利用前件云发生器得到待测样本在该属性下对每类样本的确定度期望。再次,给出一种正态云模型交叠度计算方法,用确定度最大类的正态云模型与其他种类的最大交叠度作为对全集的信任度。最后,对确定度进行归一化得到待测样本的BPA。实验结果验证了该方法的有效性,此外,在样本数据较少情况下也能有效生成BPA。
