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bayes网络     
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  bayesian networks
     2. A Markov chains Monte Carlo(MCMC) method for learning Bayesian networks is presented.
     2.给出了Bayes网络学习的Markov链Monte Carlo(MCMC)方法。
短句来源
     MCMC approach to Bayesian networks learning
     Bayes网络学习的MCMC方法
短句来源
     The Research Based on the Project Investment Risk Evaluation and Decision Method of Bayesian Networks
     基于Bayes网络的项目投资风险评估与决策方法研究
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     An Aerial Image Understanding Model Based on Bayesian Networks
     基于Bayes网络的航空图象理解模型
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     The Application of Bayesian Networks in Biochip
     Bayes网络在生物芯片中的应用
短句来源
更多       
  bayes network
     Evaluation of Enterprise Capability Based on Bayes Network
     基于Bayes网络的企业能力评估
短句来源
     Application of bayes network on estimation of machine fault probability
     Bayes网络在机械故障概率估计中的应用
短句来源
     A Spam Filtering Algorithm Based on AIS and Bayes Network
     一种基于AIS和Bayes网络的垃圾邮件过滤算法
短句来源
     Research on the method of Project Risk Evaluaton Based on the Bayes Network
     基于Bayes网络的项目风险评估方法研究
短句来源
     The MLE Algorithm on the Bayes Network for Machine Fault Diagnosis
     用于机械故障诊断Bayes网络的MLE学习方法
短句来源
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  bayesian network
     Research on the Theory of Bayesian Network and It's Application in Object Detection
     Bayes网络理论及其在目标检测中应用研究
短句来源
     Application Research and on Subjective Bayesian Network in Pervasive Computing
     主观Bayes网络在普适计算中的应用研究
短句来源
     Research on Learning Bayesian Network and Its Application in Text Detections
     Bayes网络学习及其在文本检测中的应用研究
短句来源
     3. The mixtures of factor analyzers is a Bayesian network with special structures.
     3.研究了两种特殊结构的Bayes网络模型,混合因子分析模型和独立分量分析模型。
短句来源
     The Integration of Bayesian Network s &Relational Models:Probabilistic Rel ational Models
     Bayes网络与关系模型的集成:概率关系模型
短句来源
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  bayes net
     In the paper,the methods is presented to deploy Bayes Net to the hypermedia educational system.
     文章讨论了在笔者所设计和实现的自适应教育超媒体系统中,应用Bayes网络处理学生模型中非确定因素的方法。
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      bayesian networks
    This paper presents a new framework on modeling uncertainty in ontologies based on bayesian networks (BN).
          
    Using Bayesian networks to model promising solutions from the current population of the evolutionary algorithms can ensure efficiency and intelligence search for the optimum.
          
    Franco Taroni, Colin Aitken, Paolo Garbolino, Alex Biedermann: Bayesian networks and probabilistic inference in forensic science
          
    Assessing the foundation for Bayesian networks: a challenge to the principles and the practice
          
    Learning Bayesian networks using various datasources and applications to financial analysis
          
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      bayes network
    In this paper, an "isomorphic" chain graph (ICG) model is introduced to account for correlation between samples by linking site-specific Bayes network models.
          
    A Bayes network can be viewed as a knowledge representation because it encodes the joint probability distribution.
          
    By the definition of a Bayes network this product is the probability of the current complete assignment.
          
    Bayes Network is a graphical model that depicts conditional dependencies among the concerned random variables, thus Bayesian.
          
    Bayes Network learning using various search algorithms and quality measures.
          
    更多          
      bayesian network
    Application of bayesian network learning methods to land resource evaluation
          
    All these prove the method is feasible and efficient, and indicate that Bayesian network is a promising approach for land resource evaluation.
          
    Uncertainty modeling based on Bayesian network in ontology mapping
          
    Research on Bayesian network based user's interest model
          
    On the basis of analyzing the existing users' interest models and some basic questions of users' interest (representation, derivation and identification of users' interest), a Bayesian network based users' interest model is given.
          
    更多          
      bayes net
    Accordingly, the Bayes net is divided into parts, which are analyzed separately.
          
    A Bayes net for our track graph can look like the Bayes net in Figure 6.
          
    A Bayes net for 30 movies from the Netflix prize dataset.
          
    A regular Bayes net that captures the relations between system variables at any time slice t.
          
    A two-slice temporal Bayes net that captures the acrosstime relations defined by the state equation model of the dynamic system.
          
    更多          


    A Probability

    针对手写签名的随机性和信息的不完备性,提出了将Bayes网络与前馈神经网络相结合的概率神经网络模型.论述了建模的理论基础、模型结构、训练算法及其简化算法.概率神经网络可计算待测签名样本为真(或伪)签名的最大可能性,进而确定其所属类别

    Power supply is a significant technology issue in optical fiber transmission network. Two methods of power supply systems including network power supply and local power supply systems are discussed in this paper. Local power supply system is optimal choice in optical access network.This paper proposes a structure of power supply monitoring system using Bayes network considering fault detection of power supply system in optical access network.Theoretical analysis is made and an implemention scheme is presented....

    Power supply is a significant technology issue in optical fiber transmission network. Two methods of power supply systems including network power supply and local power supply systems are discussed in this paper. Local power supply system is optimal choice in optical access network.This paper proposes a structure of power supply monitoring system using Bayes network considering fault detection of power supply system in optical access network.Theoretical analysis is made and an implemention scheme is presented.

    供电是光纤接入网中的一个重大技术问题。文中讨论了供电的两种方式 ,即网络供电方式和本地供电方式。对于光纤接入网 ,本地供电结构是一种较为理想的方案 ,但对本地供电网络监控则又是一个技术难点。文中设计了一种采用Bayes网络的电源监控系统网络结构 ,对网络进行了理论分析 ,并给出了具体的实现方案。

    As a knowledge representation framework and a kind of probability inference engine, Bayesian networks are widely used in applications for reasoning and decision making with inherent uncertainty. Since the exact algorithms of probability inference in Bayesian networks is NP-hard, as the topology of the network becomes more dense, the run-time complexity of probabilistic inference increases dramatically and real-time decision making eventually becomes prohibitive, so many approximate algorithms based on simulation...

    As a knowledge representation framework and a kind of probability inference engine, Bayesian networks are widely used in applications for reasoning and decision making with inherent uncertainty. Since the exact algorithms of probability inference in Bayesian networks is NP-hard, as the topology of the network becomes more dense, the run-time complexity of probabilistic inference increases dramatically and real-time decision making eventually becomes prohibitive, so many approximate algorithms based on simulation or model simplification are proposed. The method discussed in this paper is based on the model simplification of arc removal. In this method, a subset of arcs are selected and removed, which simplifies the network structure and we obtain an approximate network, then any probability inference algorithm can be applied to this approximate network to get a solution within the error bound we predefined. By using the Kullback-Leibler information divergence as the measure of the difference between two probability distributions, this paper discusses the multiple arc removal problem in the gen eral case and presents the optimal parameters for the approximate network. Final ly, a heuristic algorithm is provided which searches a set of arcs to be removed under the upper bound on the probability error allowed.

    弧的删除是一种对 Bayes网络模型进行近似的方法 .文中以 Kullback- L eibler偏差作为近似网络和原网络概率分布误差的测度 ,给出了近似网络在此测度意义下的最优参数 .同时 ,也给出了通过对原网络删除多条弧进行近似的启发式算法 ,当给定一个误差上界时 ,可以使用此算法寻找满足误差要求的近似网络

     
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