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。
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.
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。
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.
该推理模型前级采用神经网络并行子网，用于目标的预分类，后级采用证据理论用于多周期的不确定性推理和概率的全局分配。
The forestage of the fusion model completes target presort and its post-stage is used to multi-period uncertainty inference and the whole set distribution of probability.
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