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bayesian network inference
相关语句
  贝叶斯网络推理
     Design and Implementation of Bayesian Network Inference Platform Based on Bucket Elimination
     基于桶消元的贝叶斯网络推理平台的设计与实现
短句来源
     By this model, the author adapted the Bayesian Network inference platform set by Decision Systems Laboratory, University of Pittsburgh, analysed some data, proved its efficiency and draw a outline design on inference diagram system as well.
     利用该模型本文采用Decision Systems Laboratory, University of Pittsburgh所开发的贝叶斯网络推理平台GeNIe对一些设备的实测数据进行了故障诊断分析,验证了该模型的有效性。 最后对推理诊断系统做出了总体设计。
短句来源
     The data fusion of diferent sensors was delt first,their fusion results were fused again with bayesian network inference algorithm and the final fusion result can be gained according to the probability values of different variable states.
     首先对各传感器的数据分别进行融合,然后应用贝叶斯网络推理算法对多种传感器融合结果进行融合计算,最后根据假定变量各状态的概率取值来判断目标平台类型.
短句来源
  “bayesian network inference”译为未确定词的双语例句
     Simplification on Bayesian network inference
     Bayesian网推理中的化简方法
短句来源
     A Simulation Algorithm for Bayesian Network Inference
     贝叶斯网络推理的一种仿真算法
短句来源
     Approximate algorithm for Bayesian network inference
     贝叶斯网络的一种近似推理算法
     (2) By combining the Bayesian network’s stochastic simulating inference algorithm based on forward sampling and time-sequence simulating algorithm of power system reliability assessment, approximate Bayesian network inference algorithm for time-sequence simulation (ABNIATS) is proposed.
     2.将采用前向采样的贝叶斯网络随机模拟推理算法与电力系统可靠性评估中的时序模拟法相结合,提出了适合于大型电力系统可靠性评估的贝叶斯网络时序模拟近似推理算法(简称时序模拟推理算法)。
短句来源
  相似匹配句对
     Simplification on Bayesian network inference
     Bayesian网推理中的化简方法
短句来源
     Temporal Bayesian network and probability inference
     时间贝叶斯网络及其概率推理
短句来源
     Approximate algorithm for Bayesian network inference
     贝叶斯网络的一种近似推理算法
     A Simulation Algorithm for Bayesian Network Inference
     贝叶斯网络推理的一种仿真算法
短句来源
     Inference and Algorithm for te Dynamic Bayesian Network
     贝叶斯网络推理与算法
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  bayesian network inference
We propose a new method of sensor planning for mobile robot localization using Bayesian network inference.
      
Sensor planning for mobile robot localization using Bayesian network inference
      
We also clearly separate probabilistic inference tasks from other computations so that arbitrary Bayesian network inference algorithms can be used.
      
We now turn to the important subject of handling determinism in Bayesian network inference.
      
The queries generated by Shachter and Peot's method can be answered by using arbitrary Bayesian network inference algorithms.
      
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The notion "plan" in AI (Artificial Intelligence) was introduced to intrusion detection. The model of plan recognition for intrusion detection by using alert correlation analysis was built based on prerequisites and consequences of intrusions and Bayesian Network inference model. As a result, missed key alerts caused by weaknesses in IDS detection policies and holes in IDS network coverage were gotten back, real attack scenarios were reconstructed, future action or intrusion intention was predicted...

The notion "plan" in AI (Artificial Intelligence) was introduced to intrusion detection. The model of plan recognition for intrusion detection by using alert correlation analysis was built based on prerequisites and consequences of intrusions and Bayesian Network inference model. As a result, missed key alerts caused by weaknesses in IDS detection policies and holes in IDS network coverage were gotten back, real attack scenarios were reconstructed, future action or intrusion intention was predicted ,and appropriate responses to their actions were planned.

将AI领域中的规划概念引入入侵检测 ,建立了入侵检测的规划识别模型 ,采用因果告警关联分析和贝叶斯网推理模型实现规划识别 ,以找回因入侵检测自身的检测策略不足和网络覆盖范围漏洞而丢失的关键告警 ,重新构建了实际的攻击场景 ,并能预测攻击者的下一步行为或攻击意图 ,从而起到了提前预警的作用

In adaptive E-Learning system, the largest problem in the establishment of student learning model is how to deal with so many uncertain factors. In this paper, Bayesian Networks inference mechanism is used to deal with these uncertain factors.

在适应性E-Learning系统中,建立学生学习模型的过程中难度最大的是处理众多的不确定因素,本文运用了贝叶斯网络的推理机制来处理这些不确定因素.

On the basis of Shenoy-Shafe valuation-algebras axioms, valuation-algebras in BN (Bayesian network) inference structure are defined. A valuation-algebras model on probabilistic inference in BN is put forward, which includes four processes, namely, inference structure transformation, valuating initialization, consistency message propagation and absorption, and local computation of probabilistic inference. Corresponding algorithms are constructed and computation methods of...

On the basis of Shenoy-Shafe valuation-algebras axioms, valuation-algebras in BN (Bayesian network) inference structure are defined. A valuation-algebras model on probabilistic inference in BN is put forward, which includes four processes, namely, inference structure transformation, valuating initialization, consistency message propagation and absorption, and local computation of probabilistic inference. Corresponding algorithms are constructed and computation methods of joint probability and condition probability are concluded. The methods put forward are accounted for with an example at the end of the paper. The proposed computation models will supply new local computation methods for Bayesian network probabilistic inferences.

在Shenoy-Shafer赋值代数公理基础上,定义了贝叶斯网(Bayesian network,BN)推理结构上的赋值代数;提出BN上概率推理的赋值代数模型,该模型包括推理结构转变、赋值初始化、一致性消息全局传播与吸收以及概率推理的局部计算四个环节,建立了相应的算法以及联合概率与条件概率的计算方法;最后通过例子说明文章所提出的方法.所提出计算模型为贝叶斯网的概率推理提供了一种新的局部计算方法.

 
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