| 1. | Trust evaluation model based on dempster - shafer evidence theory
证据理论的信任评估模型 |
| 2. | Solving of multi - sensor data fusion problem by using dempster - shafer method
解多传感器数据融合问题 |
| 3. | Research on the evaluation of risk - return based on dempster - shafer theory
基于证据理论的风险收益评价模型及其应用 |
| 4. | Research on fault diagnosis method based on dempster - shafer evidential theory
证据理论的信息融合在设备故障诊断中应用 |
| 5. | Time - space data fusion and object recognition based on matrix analysis and dempster - shafer evidence theory
证据理论的时空数据融合及目标识别 |
| 6. | We researched on a new neural network shape recognition system based on dempster - shafer theory , which integrated the advantages of d - s theory and neural network
为了验证我们的思想，研究了基于d ? s证据理论的神经网络形状识别系统。 |
| 7. | Multisensor information is fused in temporal field by combing dempster - shafer theory and neural networks in order to conduct recognition and classification tasks
将dempster - shafer理论与神经网络相结合，在时间域对多传感器的多次测量进行融合，以进行识别分类。 |
| 8. | Furthermore , dempster - shafer ( d - s ) method which is used to identify objects in multi - sensor data fusion is elaborated . different situations in homogeneous and
此外,该文还详细阐明了在多传感器数据融合中目标识别的证据推理方法,对同类证据及不同类证据融合识别的各种情况分别进行了分析和讨论。 |
| 9. | From the work mentioned above , the paper independently gives a new method to generate belief functions based on rough set . and it is accordant with the requirement of dempster - shafer evidence theory
作者还独立提出了一种基于粗糙集理论的信任函数构造方法，并分析证明了其完全符合证据理论的要求。 |
| 10. | The application of multisensor information fusion of dempster - shafer evidential reasoning to sliding mode control with measuring noise was investigated , which helps to depress the uncertainty of the sliding mode function
摘要研究了d - s证据推理多传感器信息融合方法在存在量测噪声的滑模控制中的应用，它有助于削弱模函数的不确定性。 |
