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  probabilistic reasoning
    PROBABILISTIC REASONING IN BAYESIAN NETWORKS: BELIEF UPDATING IN SINGLY CONNECTED CAUSAL POLYTREE
    在贝叶斯网络上的概率推理:在单一连接因果树上的确信更新
短句来源
    During the study of incidence calculus theory, we firstly clarified original incidence calculus and the probabilistic reasoning mechanism on it. We then introduced the improvement of generalized incidence calculus theory (GICT) proposed by Liu~[18], which establishes incidence calculus theory on Lukasiewicz's three valued logic.
    本文首先阐述了原始的发生率计算理论及其上的概率推理机制,然后引入Liu对该理论的改进,以Lukasiewicz三值逻辑为基础,并提出了这个扩展的理论与证据理论之间的等价关系。
短句来源
    Basing on the theory discussed above, we analysed the probabilistic reasoning of IICT, and then proposed the relationship between the two interval incidence calculus theories, and the probabilistic reasoning mechanism according to the probabilistic reasoning of IICT.
    在上面提到的这些知识基础上,我们分析了IICT之上的概率推理,并提出IICT与IGICT之间的关系,以及由IICT的概率推理推出IGICT的概率推理机制。
短句来源
    Then the feature of AntNet algorithm is primary analyzed and two shortages in AntNet is presented: the first, AntNet only present the probabilistic reasoning feature in computational intelligence, the complementary feature is not presented.
    侧重分析了基于Q-学习的蚂蚁网络路由算法的特征,指出蚂蚁网络路由算法的两点不足:一是只体现了计算智能中的概率推理特征,并没有体现算法的互补性;
短句来源
    The concept of soft computing and its three basic constituents: fuzzy logic, neural networks and probabilistic reasoning are introduced. The article then discusses a new style fuzzy controller based on soft computing and its application.
    介绍了软计算的概念及构成软计算的三个组成部分:模糊逻辑、神经网络和概率推理,并讨论了以软计算为基础的新一代模糊控制器.
短句来源
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  probability reasoning
    Application of Bayesian Network and its Probability Reasoning to Intelligent Tutoring System
    贝叶斯网及其概率推理在智能教学中的应用
短句来源
    In Expert system,usually probability is defined as subjective credit degree of experts to evidence and regulation,and Bayes theorem is key solution in probability reasoning.
    在专家系统中,概率一般解释为专家对证据和规则的主观信任度,在概率推理中起着支撑作用的是贝叶斯定理。
短句来源
    second, the bayes network has its mature probability reasoning algorithms; third, the bayes network is liable to present the problems about fault diagnosis;
    第二,贝叶斯网络有成熟的概率推理算法:第三,贝叶斯网络更适合于表达设备故障诊断问题;
短句来源
    The approach presnted in this paper can satisfy the exact probability reasoning; contain the uncertainty of the information, effectively avoid the unknown for the relationship among the rules, and the computing complexity of its briefest inference is linear to the number of inferential nodes.
    介绍的不确定推理方法可以包容精确的概率推理、容忍信息的不确定性、有效地避免推理规则之间的相互关系问题 ,并且使认知结构最简推理的计算复杂度与推理节点个数成线性关系
短句来源
    The authors firstly outline BBN and probability reasoning, then propose and implement our intelligent tutoring system that uses BBN as student models, and emphasize the structure and functions and probability reasoning algorithm of student models.
    对贝叶斯网及其概率推理进行了简述,提出并实现了一种以贝叶斯网为学生模型的智能教学系统,并重点介绍了学生模型的结构、功能和概率推理算法.
短句来源
  probability inference
    Temporal Bayesian network and probability inference
    时间贝叶斯网络及其概率推理
短句来源
    1. Owing to the complexity of the probability inference in Bayesian networks is NP, some approximating methods are necessary in practice.
    1.由于在一般结构的Bayes网络模型中进行概率推理计算是一个NP问题,因此近似计算是十分必要的。
短句来源
    Bayesian network as,a very useful tool in data mining,can provide qualitative and quantitative relationship between attributes and probability inference.
    贝叶斯网络是数据采掘的一个非常有效的工具,它能够定性和定量地分析属性之间的依赖关系,进行概率推理
短句来源
  probabilistic inference
    PROBABILISTIC INFERENCE AND INFLUENCE DIAGRAMS
    概率推理与影响图
短句来源
    After discussing the theory foundations of the certainty factor model and its drawbacks, the equivalence of the probabilistic inference equation of a Noisy-OR model, a simplified BN model, and the inference equation of a certainty factor model is argued. The advantages of BNs over the certainty factor models are discussed in knowledge representation and acquisition and their inference.
    讨论了确信因子模型的理论基础,分析了确信因子模型的局限性,论证了Noisy-OR模型(Bayes网络的一种简化模型)的概率推理公式与确信因子模型的推理公式的等价性,从知识的表示、推理、获取三个方面论述了Bayes网络相对于确信因子模型的优势。
短句来源
    Bayesian Networks is a model that efficiently represents knowledge and probabilistic inference and is a popular graphics decision-making analysis tool.
    贝叶斯网络是在不确定性环境下有效的知识表示方式和概率推理模型,是一种流行的图形决策化分析工具。
短句来源
    The paper discusses the applications of influence diagrams to probabilistic inference, and information with the inference.
    本文讨论了影响图理论在概率推理过程中的应用和要涉及的信息及信息量。
短句来源
    PPJT provides a new theoretic tool for implementation of probabilistic inference in the common com- plicated network.
    PPJT算法为实现一般复杂网络中的概率推理提供了一种新的理论工具。
短句来源

 

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