• Fuzzy evidence (D-S) theory is based on nonempty sets.

    模糊证据(D - S)理论基于非空集合。

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  • The diagnosis results of fuzzy methods are fused based on D-S evidence theory.

    运用D S证据理论将用不同模糊方法得出的诊断结果进行融合。

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  • This D-S decision tree is a new classification method adapted to the uncertain data.

    实验结果表明D- S决策树分类算法能有效的对不确定数据进行分类。

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  • Then, all the classification results are integrated by the use of D-S combination rule.

    然后,利用证据组合规则对多分类器进行集成。

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  • In this article, the D-S evidence theory is used to judge the reliability of scientific hypothesis.

    本文将D - S证据理论应用于判断科学假说的可靠性。

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  • This paper Studies and analyzes on data fusion for Ultrasonic adhesive detecting by D-S theory of evidence.

    采用D-S证据理论,提出了利用声激励和超声探头检测金属与非金属粘接状态的融合方法,并进行了验证分析。

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  • The method of using history test datum to make prior distribution and d-s evidence fusion theory are discussed.

    讨论了由历史试验数据确定先验分布的方法和多源信息的D—S证据融合方法。

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  • Evidence modeling has become a bottleneck problem of restricting the application of D-S evidence theory currently.

    证据建模已经成为当前制约d—s证据理论广泛应用的一个瓶颈问题。

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  • The fusion belief function assignment is gotten by using D-S rule and fuzzy logic theory, and fault component is found.

    再利用D - S联合规则结合模糊逻辑理论,得到融合后的信度函数分配,从而确定故障元件。

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  • Considering the disadvantages of the weighed D-S theory, a best method of obtaining evidence weight value is presented.

    针对加权证据理论的这一研究不足,提出了一种求取最佳证据权值的方法。

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  • Then D-S evidence theory is demonstrated, which gives an improvement in fusing the recognition results of separate features.

    利用D - S证据推理理论对单个特征的识别结果进行融合,有效改进了识别效果。

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  • This paper detailedly introduces D-S evidence theory, and discusses the application of D-S evidence theory in vehicles identify.

    论文详细地介绍了D - S证据理论,并探讨了D - S证据理论在车辆身份识别系统中的运用。

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  • It fuses single fault degree by D-S evidence theory and calculates continuous fault degree. The line of maximum degree is the fault line.

    应用d - S证据理论对单次故障度进行有效融合,计算出连续故障度,连续故障度最大的线路就是故障线路。

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  • D-S evidence Theory can integrate all kinds of information coming from every expert. It made the evaluation results much more reasonable.

    证据理论综合了来自各个专家的评价信息,能够使得评价过程更加合理。

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  • This paper gives a data fusion structure based on RBF neural network and D-S inference and its application in the fault diagnosis of bearing.

    提出一种基于RBF神经网络和D - S证据理论相结合的数据融合结构应用于轴承故障诊断。

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  • The key problem to D-S reasoning is basic probability assignment function, so the algorithm implementation of D-S reasoning is a esrious problem.

    在基于D-S推理的信息融合中,其关键问题是基本概率赋值函数的构造。

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  • The paper has improved the contexture methodology of basic probability of D-S Reasoning when its application in information temporal-spatial fusion.

    论文改进了应用证据理论进行信息时空融合诊断时基本概率赋值的构造方法。

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  • For data fusion algorithms of multi-sensors, the D-S rule is widely used extensively. But it can not resolve the problem of feature collision ideally.

    在多传感器特征信息融合算法中,D - S理论得到了广泛应用,但该理论在处理多特征冲突问题时识别效果不十分理想。

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  • The decision fusion level module USES D-S evidence theory to fuse the local diagnostic results of feature fusion level, then get the final diagnostic results.

    决策级采用D - S证据理论的方法对特征级局部诊断的结果加以融合,得到最终的诊断结果。

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  • In order to resolve the problem of fuzzy logic that reasoning method is too simple to take full advantage of useful information, apply D-S theory to fuzzy reasoning.

    为了解决模糊逻辑推理过程中组合证据的方法过于简单容易丢失有用信息的问题,采用D - S证据理论进行模糊推理。

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  • Aim at the problem of detecting for distant small target with very low SNR, a method of two color IR small target fusion detection using D-S evidence theory is proposed.

    针对远距离低信噪比条件下目标检测难的实际问题,提出采用D - S证据理论的双色红外小目标融合检测方法。

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  • Based on D-S evidence theory in data fusion technology, this paper applies it to distributed intrusion detection systems and gives a network intrusion early warning model.

    本文以数据融合技术中的D - S证据理论为基础,将其运用于分布式入侵检测系统中,提出了基于D - S证据理论的网络入侵预警模型。

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  • Aiming at the complexity and fuzziness of modern radar signals and the redundancy characteristic of the signals on time, fuzzy matching is combined with D-S evidence theory.

    针对现代雷达信号的复杂性和模糊性以及信号在时间上的冗余性等特点,将模糊匹配和D - S证据理论相结合。

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  • We use a parallel and with feedback fusion system architecture, cascade D-S evidence theory to be fusion algorithm. Finally, a graphic target recognition system is realized.

    系统采用有反馈的全并行融合系统结构,以分级式d S证据推理为数据融合算法,最终实现一个图形化的目标识别系统。

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  • The conflict factor of D-S evidence theory is applied to constructing an adaptive ultrasonic sensor model for the navigation of mobile robots in narrow unknown environments.

    针对移动机器人在未知狭窄环境中的导航问题,利用证据理论中的矛盾因子,给出了一个自适应超声波传感器模型。

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  • D-S evidence theory is applied in the multi-sensor data fusion, the generalized method of the data fusion is proposed and applied in the fault diagnosis of the hydraulic pump.

    将D - S证据理论应用于多传感器数据融合,提出了多传感器数据融合一般化方法,并将其应用于液压泵故障诊断。

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  • D-S evidence theory was applied in the multi-sensor data fusion, the generalized method of the data fusion was proposed and applied in the fault diagnosis of the hydraulic pump.

    将D - S证据理论应用于多传感器数据融合,提出了多传感器数据融合一般化方法,并将其应用于液压泵故障诊断。

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  • A multisensor data fusion method based on Dempster-Shafer evidence theory is described, and an improved algorithm of D-S is put out to solve the dependent information in data fusion.

    阐述了基于D - S证据理论的多传感器信息融合算法,提供一种基于D - S理论的改进方法以解决融合信息的相关性问题。

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  • On a process of identifying the sea surface target by using D-S evidence theory, the method of how to determine basic probability assignment (BPA) by measured data of sensor is studied.

    在应用D S证据理论识别海面目标的过程中,重点研究了如何通过传感器数据实测值来确定基本概率分配函数(BPA)的方法。

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  • On a process of identifying the sea surface target by using D-S evidence theory, the method of how to determine basic probability assignment (BPA) by measured data of sensor is studied.

    在应用D S证据理论识别海面目标的过程中,重点研究了如何通过传感器数据实测值来确定基本概率分配函数(BPA)的方法。

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