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
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
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
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
准确判别燃爆状态是测量燃爆延滞期并计算爆发点参数的关键。针对单一传感器判别效果不佳、多个传感器判别结果相互冲突的问题,利用D-S(Dempster-Shafer)证据理论对冲突证据进行联合判别。首先根据含能材料燃爆特性和爆发点测试原理,设...准确判别燃爆状态是测量燃爆延滞期并计算爆发点参数的关键。针对单一传感器判别效果不佳、多个传感器判别结果相互冲突的问题,利用D-S(Dempster-Shafer)证据理论对冲突证据进行联合判别。首先根据含能材料燃爆特性和爆发点测试原理,设计了基于温度和声音的联合判别装置;从实验数据出发,采用模型拟合提取温度特征值,以及声音信号最大值为声音特征值。其次,根据Sigmoid模型求解出BPA(Basic Probability Assignment)函数,并通过信度熵对可能存在冲突的BPA函数值进行预处理;最终,利用D-S证据理论进行燃爆状态联合判别。实验结果表明,所提方法有效提高了实验装置的鲁棒性和状态判别的置信概率,燃爆判别准确率达到了96.5%,优于温度、声音等单一传感器的判别效果。展开更多
To aim at the multimode character of the data from the airplane detecting system, the paper combines Dempster- Shafer evidence theory and subjective Bayesian algorithm and makes to propose a mixed structure multimode ...To aim at the multimode character of the data from the airplane detecting system, the paper combines Dempster- Shafer evidence theory and subjective Bayesian algorithm and makes to propose a mixed structure multimode data fusion algorithm. The algorithm adopts a prorated algorithm relate to the incertitude evaluation to convert the probability evaluation into the precognition probability in an identity frame, and ensures the adaptability of different data from different source to the mixed system. To guarantee real time fusion, a combination of time domain fusion and space domain fusion is established, this not only assure the fusion of data chain in different time of the same sensor, but also the data fusion from different sensors distributed in different platforms and the data fusion among different modes. The feasibility and practicability are approved through computer simulation.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
多源数据是一种综合多个信息源的复杂数据类型,其主要特点是不同的信息源从不同的角度刻画了样本以及样本之间的关系(具体到配电网领域,不同量测系统针对同一节点所得到的数据是不同的,甚至存在较大差异)。提出了一种适用于配电网线损...多源数据是一种综合多个信息源的复杂数据类型,其主要特点是不同的信息源从不同的角度刻画了样本以及样本之间的关系(具体到配电网领域,不同量测系统针对同一节点所得到的数据是不同的,甚至存在较大差异)。提出了一种适用于配电网线损计算的多源数据综合利用方法,为便于数据融合,对多源量测数据进行转换;为保证量测时间断面一致性,选择同步相量测量单元(phasor measurement unit,PMU)某一量测时刻作为基准,对数据采集与监视控制(supervisory control and data acquistion,SCADA)系统数据进行时间配准与数据填充操作,对智能电表数据采用“量测值+预测值”方式进行时标对齐;对时序数据进行滤波,获得较为准确的配电网数据;基于登普斯特-沙夫特(dempster-shafter,D-S)证据理论法实现多源数据融合。以某10 kV配电网为算例分析计算了配电网线损,结果表明,所提方法可较好地完成多源数据的综合利用,提高配电网线损计算的准确性。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(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 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.
文摘准确判别燃爆状态是测量燃爆延滞期并计算爆发点参数的关键。针对单一传感器判别效果不佳、多个传感器判别结果相互冲突的问题,利用D-S(Dempster-Shafer)证据理论对冲突证据进行联合判别。首先根据含能材料燃爆特性和爆发点测试原理,设计了基于温度和声音的联合判别装置;从实验数据出发,采用模型拟合提取温度特征值,以及声音信号最大值为声音特征值。其次,根据Sigmoid模型求解出BPA(Basic Probability Assignment)函数,并通过信度熵对可能存在冲突的BPA函数值进行预处理;最终,利用D-S证据理论进行燃爆状态联合判别。实验结果表明,所提方法有效提高了实验装置的鲁棒性和状态判别的置信概率,燃爆判别准确率达到了96.5%,优于温度、声音等单一传感器的判别效果。
文摘To aim at the multimode character of the data from the airplane detecting system, the paper combines Dempster- Shafer evidence theory and subjective Bayesian algorithm and makes to propose a mixed structure multimode data fusion algorithm. The algorithm adopts a prorated algorithm relate to the incertitude evaluation to convert the probability evaluation into the precognition probability in an identity frame, and ensures the adaptability of different data from different source to the mixed system. To guarantee real time fusion, a combination of time domain fusion and space domain fusion is established, this not only assure the fusion of data chain in different time of the same sensor, but also the data fusion from different sensors distributed in different platforms and the data fusion among different modes. The feasibility and practicability are approved through computer simulation.
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.
文摘多源数据是一种综合多个信息源的复杂数据类型,其主要特点是不同的信息源从不同的角度刻画了样本以及样本之间的关系(具体到配电网领域,不同量测系统针对同一节点所得到的数据是不同的,甚至存在较大差异)。提出了一种适用于配电网线损计算的多源数据综合利用方法,为便于数据融合,对多源量测数据进行转换;为保证量测时间断面一致性,选择同步相量测量单元(phasor measurement unit,PMU)某一量测时刻作为基准,对数据采集与监视控制(supervisory control and data acquistion,SCADA)系统数据进行时间配准与数据填充操作,对智能电表数据采用“量测值+预测值”方式进行时标对齐;对时序数据进行滤波,获得较为准确的配电网数据;基于登普斯特-沙夫特(dempster-shafter,D-S)证据理论法实现多源数据融合。以某10 kV配电网为算例分析计算了配电网线损,结果表明,所提方法可较好地完成多源数据的综合利用,提高配电网线损计算的准确性。