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This paper addresses issues in constructing a Bayesian network domain model for diagnostic purposes from expert knowledge.


TailoredtoFit Bayesian Network Modeling of Expert Diagnostic Knowledge


The object class is generatively modeled using a simple Bayesian network with a central hidden node containing location and scale information, and nodes describing object parts.


Our algorithm is implemented in a commercial Bayesian Network software package, AgenaRisk, which allows model construction and testing to be carried out easily.


In particular, to determine Jeffrey's prior for this model family, we show how to compute the (expected) Fisher information matrix for a fixed but arbitrary Bayesian network structure.

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 Aimed at the online data from sensors of airplane pressure fueling system, an algorithm for sensor validation is presented with the help of Bayesian network(BN). The degrees of dependence and independence among all the sensors are determined. Then the accurate judgments to the system state can be deduced to guide the fault isolation. During the experiments, an incident of pressure overshoot comes forth in the entrance pipeline connected with the reservoir No.5, and the analytical result shows something... Aimed at the online data from sensors of airplane pressure fueling system, an algorithm for sensor validation is presented with the help of Bayesian network(BN). The degrees of dependence and independence among all the sensors are determined. Then the accurate judgments to the system state can be deduced to guide the fault isolation. During the experiments, an incident of pressure overshoot comes forth in the entrance pipeline connected with the reservoir No.5, and the analytical result shows something wrong with the corresponding oil height sensor. Through the succedent detection, the phenomenone that the inner resistance mismatch really occurs in the same sensor, the experiment testifies strongly that the method described above is feasible and efficient.  针对飞机地面压力加油系统传感器的实测信息 ,提出了实际环境下的传感器信息确认算法 .利用贝叶斯网络 (BN)构造传感器的相互关系 ,描述了各传感器之间相互依赖与独立的程度 ,并且对传感器参数进行动态评估 ,得出了对系统状态的准确判断 ,用于指导对故障的有效确认 .在地面试验研究过程中 ,对一起管路严重超压现象进行了成功的判断 ,证明了该方法的可行性和有效性 .  This paper describes a method for designing a model framework of situation awareness for the uninhabited combat air vehicle (UCAV) based on the objectoriented Bayesian networks(OOBN). This method is more effectively to explore a situation awareness model for multiple UCAVs coordination, and to study situation awareness of the air combat environment where there are many threatening entities. This paper also analyses the characteristic of situation awareness for UCAV, gives threat assessment module and... This paper describes a method for designing a model framework of situation awareness for the uninhabited combat air vehicle (UCAV) based on the objectoriented Bayesian networks(OOBN). This method is more effectively to explore a situation awareness model for multiple UCAVs coordination, and to study situation awareness of the air combat environment where there are many threatening entities. This paper also analyses the characteristic of situation awareness for UCAV, gives threat assessment module and steps to create the situation awareness model based on multiple UCAVs coordination.  提出了利用面向对象的贝叶斯网络构建无人战斗机的态势感知模型框架,探索了有利于多机协同作战的态势感知模型,以及作战环境具有多个不同威胁实体的态势感知;给出了无人战斗机态势感知的特点及威胁水平评估模型,以及构建基于多机协同的态势感知模型的具体步骤。  Intelligent tactical flight path planning system is proposed by integrating situation assessment with path planning. The algorithms of assessment for threat level and relative importance are established based on Bayesian networks and fuzzy logic. The flight path planning is implemented using the model predictive control depending on its receding horizon optimization and correction online. The intelligent assignment of weighting factors in cost function of path planning is developed based on fuzzy logic,... Intelligent tactical flight path planning system is proposed by integrating situation assessment with path planning. The algorithms of assessment for threat level and relative importance are established based on Bayesian networks and fuzzy logic. The flight path planning is implemented using the model predictive control depending on its receding horizon optimization and correction online. The intelligent assignment of weighting factors in cost function of path planning is developed based on fuzzy logic, which integrated situation assessment with path (planning.) The proposed intelligent tactical flight path planning system can adapt the dynamic variable situations in (battlefield.) The simulation results show the good effectiveness.  对态势评估与规划系统进行集成,提出了智能化战术飞行轨迹规划系统方案.基于贝叶斯网络和模糊推理技术,实现了战场威胁级别及其相对重要性程度的综合评估.利用模型预测控制的滚动优化和在线校正原理,实现了飞机在线飞行路径规划.建立了路径规划代价函数中加权因子的智能化分配方法,进而实现了威胁评估与路径规划之间的集成,使得路径规划系统能够自适应战场态势的动态变化.最后通过仿真验证了所提出方法的有效性.   << 更多相关文摘 
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