An improvement method for the combining rule of Dempster evidence theory is proposed. Different from Dempster theory, the reliability of evidences isn't identical; and varies with the event. By weight evidence acc...An improvement method for the combining rule of Dempster evidence theory is proposed. Different from Dempster theory, the reliability of evidences isn't identical; and varies with the event. By weight evidence according to their reliability, the effect of unreliable evidence is reduced, and then get the fusion result that is closer to the truth. An example to expand the advantage of this method is given. The example proves that this method is helpful to find a correct result.展开更多
In order to effectively deal with the conflict temporal evidences without affecting the sequential and dynamic characteristics in the multi-sensor target recognition(MSTR) system at the decision making level, this pap...In order to effectively deal with the conflict temporal evidences without affecting the sequential and dynamic characteristics in the multi-sensor target recognition(MSTR) system at the decision making level, this paper proposes a Dempster-Shafer(DS) theory and intuitionistic fuzzy set(IFS) based temporal evidence combination method(DSIFS-TECM). To realize the method,the relationship between DS theory and IFS is firstly analyzed. And then the intuitionistic fuzzy possibility degree of intuitionistic fuzzy value(IFPD-IFV) is defined, and a novel ranking method with isotonicity for IFV is proposed. Finally, a calculation method for relative reliability factor(RRF) is designed based on the proposed ranking method. As a proof of the method, numerical analysis and experimental simulation are performed. The results indicate DSIFS-TECM is capable of dealing with the conflict temporal evidences and sensitive to the changing of time. Furthermore, compared with the existing methods, DSIFS-TECM has stronger ability of anti-interference.展开更多
针对视频情感识别中存在运算复杂度高的缺点,提出一种基于时空局部二值模式矩(Temporal-Spatial Local Binary Pattern Moment,TSLBPM)的双模态情感识别方法。首先对视频进行预处理获得表情和姿态序列;然后对表情和姿态序列分别提取TSL...针对视频情感识别中存在运算复杂度高的缺点,提出一种基于时空局部二值模式矩(Temporal-Spatial Local Binary Pattern Moment,TSLBPM)的双模态情感识别方法。首先对视频进行预处理获得表情和姿态序列;然后对表情和姿态序列分别提取TSLBPM特征,计算测试序列与已标记的情感训练集特征间的最小欧氏距离,并将其作为独立证据来构造基本概率分配(Basic Probability Assignment,BPA);最后使用Dempster-Shafer证据理论联合规则得到情感识别结果。在双模态表情和姿态情感数据库上的实验结果表明,本文提出的时空局部二值模式矩可以快速提取视频图像的时空特征,能有效识别情感状态。与其他方法的对比实验也验证了本文融合方法的优越性。展开更多
[目的]揭示驱动盘龙江流域不透水表面扩张的影响因子,以及影响因子各属性值对不透水表面扩张的影响程度,并在分析驱动机制的基础上,模拟预测盘龙江流域的扩张趋势,为流域生态建设合理规划提供依据。[方法]采用Dempster—Shafer(D—S)证...[目的]揭示驱动盘龙江流域不透水表面扩张的影响因子,以及影响因子各属性值对不透水表面扩张的影响程度,并在分析驱动机制的基础上,模拟预测盘龙江流域的扩张趋势,为流域生态建设合理规划提供依据。[方法]采用Dempster—Shafer(D—S)证据理论来描述和融合多种空间数据,在已有的不透水表面(impervious surfaces,IS)信息与多种空间数据的量关系的基础上,采用数据驱动方法分配基本概率函数(basic probability assignment,BPA)。经过定义多种空间数据的BPA函数,然后采用D—S证据理论的融合规则融合多个BPA函数以获取研究区域IS的信任函数、不信任函数、不确定函数、似真函数。[结果]距道路距离,距居民点距离,距水系距离,人口密度,GDP,IS邻域单元数,坡度,高程驱动因子对盘龙江流域不透水表面的扩张影响比较大,而坡向对不透水表面扩张的影响程度变化不明显。不透水表面扩张模拟的精度达到78.04%。[结论]采用D—S证据理论方法来描述空间数据和融合多种空间数据具有比传统逻辑回归模型更好的分析和预测功能。展开更多
Dempster-Shafer evidence theory(DS theory) is widely used in brain magnetic resonance imaging(MRI) segmentation,due to its efficient combination of the evidence from different sources. In this paper, an improved MRI s...Dempster-Shafer evidence theory(DS theory) is widely used in brain magnetic resonance imaging(MRI) segmentation,due to its efficient combination of the evidence from different sources. In this paper, an improved MRI segmentation method,which is based on fuzzy c-means(FCM) and DS theory, is proposed. Firstly, the average fusion method is used to reduce the uncertainty and the conflict information in the pictures. Then, the neighborhood information and the different influences of spatial location of neighborhood pixels are taken into consideration to handle the spatial information. Finally, the segmentation and the sensor data fusion are achieved by using the DS theory. The simulated images and the MRI images illustrate that our proposed method is more effective in image segmentation.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
A new conflicting evidence fusion method is proposed for the deficiency of Dempster's rule which can not fuse the conflicting evidence. Evidence is divided into three categories:believable evidence, non-conflictin...A new conflicting evidence fusion method is proposed for the deficiency of Dempster's rule which can not fuse the conflicting evidence. Evidence is divided into three categories:believable evidence, non-conflicting evidence and conflicting evidence. The influences of these three categories of evidences on fusion results when discounted are analyzed respectively. On these bases, the evidence distance and the conjunctive conflict are utilized in sequence to recognize the believable evidence and non-conflicting evidence. The discounting factors of these two categories of evidences are set to one, which keeps the evidences support the true hypothesis to the greatest degree, and makes the fusion results focus onto the true hypothesis. Examples of some missile fault diagnosis show that the new method can effectively fuse the conflicting evidences, and is suited to fuse the relievable evidences. The new method improves the reliability and rationality of fusion results compared with traditional methods.展开更多
弹道中段目标为一个目标群,包括弹头、诱饵、碎片等,并且由于距离传感器较远,红外成像为点目标,可用信息较少,因此单一的红外传感器往往难以满足识别要求,需要融合多个传感器进行识别。针对红外多传感器的融合识别问题,本文提出了基于...弹道中段目标为一个目标群,包括弹头、诱饵、碎片等,并且由于距离传感器较远,红外成像为点目标,可用信息较少,因此单一的红外传感器往往难以满足识别要求,需要融合多个传感器进行识别。针对红外多传感器的融合识别问题,本文提出了基于增量支持向量机和D-S(increment support vector machine-Dempster-Shafer,ISVM-DS)证据理论的融合识别方法。首先,训练多个波段传感器红外特征的支持向量数据描述(support vector data description,SVDD)模型,生成壳向量并训练其ISVM模型;接着,采用ISVM模型的后验概率生成基本概率赋值(basic probability assignment,BPA);最后,利用D-S证据理论对多个证据的BPA进行融合,输出分类结果。实验结果表明,该方法能有效提高目标识别的准确性。展开更多
文摘An improvement method for the combining rule of Dempster evidence theory is proposed. Different from Dempster theory, the reliability of evidences isn't identical; and varies with the event. By weight evidence according to their reliability, the effect of unreliable evidence is reduced, and then get the fusion result that is closer to the truth. An example to expand the advantage of this method is given. The example proves that this method is helpful to find a correct result.
基金supported by the National Natural Science Foundation of China(61272011)
文摘In order to effectively deal with the conflict temporal evidences without affecting the sequential and dynamic characteristics in the multi-sensor target recognition(MSTR) system at the decision making level, this paper proposes a Dempster-Shafer(DS) theory and intuitionistic fuzzy set(IFS) based temporal evidence combination method(DSIFS-TECM). To realize the method,the relationship between DS theory and IFS is firstly analyzed. And then the intuitionistic fuzzy possibility degree of intuitionistic fuzzy value(IFPD-IFV) is defined, and a novel ranking method with isotonicity for IFV is proposed. Finally, a calculation method for relative reliability factor(RRF) is designed based on the proposed ranking method. As a proof of the method, numerical analysis and experimental simulation are performed. The results indicate DSIFS-TECM is capable of dealing with the conflict temporal evidences and sensitive to the changing of time. Furthermore, compared with the existing methods, DSIFS-TECM has stronger ability of anti-interference.
文摘针对视频情感识别中存在运算复杂度高的缺点,提出一种基于时空局部二值模式矩(Temporal-Spatial Local Binary Pattern Moment,TSLBPM)的双模态情感识别方法。首先对视频进行预处理获得表情和姿态序列;然后对表情和姿态序列分别提取TSLBPM特征,计算测试序列与已标记的情感训练集特征间的最小欧氏距离,并将其作为独立证据来构造基本概率分配(Basic Probability Assignment,BPA);最后使用Dempster-Shafer证据理论联合规则得到情感识别结果。在双模态表情和姿态情感数据库上的实验结果表明,本文提出的时空局部二值模式矩可以快速提取视频图像的时空特征,能有效识别情感状态。与其他方法的对比实验也验证了本文融合方法的优越性。
文摘[目的]揭示驱动盘龙江流域不透水表面扩张的影响因子,以及影响因子各属性值对不透水表面扩张的影响程度,并在分析驱动机制的基础上,模拟预测盘龙江流域的扩张趋势,为流域生态建设合理规划提供依据。[方法]采用Dempster—Shafer(D—S)证据理论来描述和融合多种空间数据,在已有的不透水表面(impervious surfaces,IS)信息与多种空间数据的量关系的基础上,采用数据驱动方法分配基本概率函数(basic probability assignment,BPA)。经过定义多种空间数据的BPA函数,然后采用D—S证据理论的融合规则融合多个BPA函数以获取研究区域IS的信任函数、不信任函数、不确定函数、似真函数。[结果]距道路距离,距居民点距离,距水系距离,人口密度,GDP,IS邻域单元数,坡度,高程驱动因子对盘龙江流域不透水表面的扩张影响比较大,而坡向对不透水表面扩张的影响程度变化不明显。不透水表面扩张模拟的精度达到78.04%。[结论]采用D—S证据理论方法来描述空间数据和融合多种空间数据具有比传统逻辑回归模型更好的分析和预测功能。
基金supported by the National Natural Science Foundation of China(6167138461703338)+2 种基金the Natural Science Basic Research Plan in Shaanxi Province of China(2016JM6018)the Project of Science and Technology Foundationthe Fundamental Research Funds for the Central Universities(3102017OQD020)
文摘Dempster-Shafer evidence theory(DS theory) is widely used in brain magnetic resonance imaging(MRI) segmentation,due to its efficient combination of the evidence from different sources. In this paper, an improved MRI segmentation method,which is based on fuzzy c-means(FCM) and DS theory, is proposed. Firstly, the average fusion method is used to reduce the uncertainty and the conflict information in the pictures. Then, the neighborhood information and the different influences of spatial location of neighborhood pixels are taken into consideration to handle the spatial information. Finally, the segmentation and the sensor data fusion are achieved by using the DS theory. The simulated images and the MRI images illustrate that our proposed method is more effective in image segmentation.
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A new conflicting evidence fusion method is proposed for the deficiency of Dempster's rule which can not fuse the conflicting evidence. Evidence is divided into three categories:believable evidence, non-conflicting evidence and conflicting evidence. The influences of these three categories of evidences on fusion results when discounted are analyzed respectively. On these bases, the evidence distance and the conjunctive conflict are utilized in sequence to recognize the believable evidence and non-conflicting evidence. The discounting factors of these two categories of evidences are set to one, which keeps the evidences support the true hypothesis to the greatest degree, and makes the fusion results focus onto the true hypothesis. Examples of some missile fault diagnosis show that the new method can effectively fuse the conflicting evidences, and is suited to fuse the relievable evidences. The new method improves the reliability and rationality of fusion results compared with traditional methods.
文摘弹道中段目标为一个目标群,包括弹头、诱饵、碎片等,并且由于距离传感器较远,红外成像为点目标,可用信息较少,因此单一的红外传感器往往难以满足识别要求,需要融合多个传感器进行识别。针对红外多传感器的融合识别问题,本文提出了基于增量支持向量机和D-S(increment support vector machine-Dempster-Shafer,ISVM-DS)证据理论的融合识别方法。首先,训练多个波段传感器红外特征的支持向量数据描述(support vector data description,SVDD)模型,生成壳向量并训练其ISVM模型;接着,采用ISVM模型的后验概率生成基本概率赋值(basic probability assignment,BPA);最后,利用D-S证据理论对多个证据的BPA进行融合,输出分类结果。实验结果表明,该方法能有效提高目标识别的准确性。
