belief network
英 [bɪˈliːf ˈnetwɜːk]
美 [bɪˈliːf ˈnetwɜːrk]
网络 信任网络; 信念网络; 又称信念网络; 信度网; 置信网络
双语例句
- Analysis of Quality Management Risk in Large Construction Projects Based on Bayesian Belief Network& A Case Study of Beijing-Shanghai High-Speed Railway Project
基于贝叶斯网络的建设项目质量管理风险因素分析&以京沪高速铁路建设项目为例 - This paper presents an IR model that extends the basic belief network model with synonym-based evidence.
以同义词为证据扩展基本信念网络模型，得到一个扩展的信念网络检索模型。 - A Multi-Level Belief Network Model for Knowledge Acquisition
知识获取的多层证据网络模型 - Combining fuzzy method and the Bayesian belief network, a novel anomaly detection model is devised.
提出了一种新型异常检测模型。 - With its local computation, each belief network node can be regarded as a processor.
由于其局部计算特性，每个信度网节点可视为一个处理器进行并行运算。 - Modeling with Bayesian belief network has been a powerful tool to solve many uncertainty problems.
使用贝叶斯网建模已成为解决许多不确定性问题的强有力工具。 - The Causality Diagram theory, which adopted graphical expression of knowledge and direct causality intensity of causality, overcomes some shortages in Belief Network and has evolved into a mixed causality diagram methodology coped with discrete and continuous variable.
在因果图理论中，采用了图形化和直接因果强度来表达知识和因果关系，它克服了贝叶斯网的一些不足，已经发展成了一个能够处理离散变量和连续变量的混合模型。 - Uncertainty knowledge representation can be divided into two parts. One of them is knowledge representation based on probability theory such as belief network model, dynamic causality diagram model, markov network model, the method used in PROSPECTOR specialist system and so on.
不确定的知识表达可分为两大类：一类是基于概率的方法，包括信度网、因果图、马尔可夫网以及在PROSPECTOR中使用的方法等。 - Experimental results indicate that the expanded model has better retrieval performance than the basic belief network model's.
实验证明，扩展模型的检索性能优于基本模型。 - Algorithm to Transform Dynamic Causality Diagram Into Belief Network
因果图转换为信度网的算法 - It is mainly of two kinds, Naive Bayesian Classification and Bayesian Belief Network Classification.
它主要有两种分类方法：一种为朴素贝叶斯分类，另一种为贝叶斯信念网络分类。 - Among the probabilistic approaches, Pearl's belief network is the most representative, due to its rigorousness and consistence in theory, the efficient local computation mechanism and intuitive graphical expression of knowledge.
在概率方法中，信度网由于其理论的健壮性和一致性、有效的局部计算机制和直观的图形化知识表达方式而日益受到重视。 - Belief Network Method in Uncertainty Management
不精确推理中的信度网络方法 - A Bayesian Belief Network ( BBN) is a graphic model that encodes joint probability distribution among uncertain variables, it express a potential dependent relationship between variables.
贝叶斯网是用来表示不确定变量集合联合概率分布的图形模式，它反映了变量间潜在的依赖关系。 - Bayesian Belief Network Model Learning, Inference and Applications
贝叶斯网模型的学习、推理和应用 - Among of uncertainty knowledge representation and reasoning models based on probability theory, belief network model is representative, due to its rigorousness and consistence in theory, the efficient computation mechanism and intuitive graphical expression of knowledge.
在基于概率论的不确定性推理理论中，信度网模型因其具有理论上的严格性和一致性，具有有效地局部计算机制和直观的图形化知识表达，正日益受到高度重视。 - Application of belief network in pattern recognition classifier
置信度网络在判别分析中的应用 - For solving the intelligent prediction and control issue of network congestion, the AI technology is introduced into the network management system, and the belief network modeling of telecommunication network congestion and corresponding decision network modeling are present.
本文以四川德阳、达川、宜宾电信网本地网管系统的工程为背景，将人工智能技术引入网管系统，主要想解决网络阻塞的智能预测及控制决策问题。 - Approximate Inference Algorithms of Belief Network ( 1)
信度网近似推理算法（上） - Many methods are used to induct belief network structures from data.
通过很多方法，可以从数据学习信度网结构。 - Some feasible methods that can simplify the model structure and reduce the learning complexity are proposed, and the application of these methods to the belief network is explained briefly.
并从实际出发，提出了几种可以简化模型结构、降低学习复杂性的可行方法，简要说明了这些方法在网络模型中的应用。 - Algorithm of Bayesian Belief Network Structure of Compressed Candidature
压缩候选的贝叶斯信念网络构造算法 - Study on Transition from Causality Diagram to Belief Network
因果图向信度网转化的方法研究 - An On-Line Structure Learning Algorithm of Belief Network
信度网结构在线学习算法 - The major contents are as follows: ( 1) With regard to the problem of low recall and precision in business information retrieval, an extended belief network based business information retrieval model has been proposed.
主要内容如下：（1）针对货源信息检索过程中的查全率、查准率低的问题，设计了基于扩展信任度网络的货源信息检索模型。 - Then introduced the basic concepts and background knowledge of Bayesian classifier by analysis several common Bayesian classifiers, in order to propose an appropriate Bayesian belief network model and algorithm applied to specific scenarios.
之后介绍了贝叶斯分类器的基本概念和背景知识，通过对几种常见的贝叶斯分类器的分析，得出了一种适用于事后审计的贝叶斯信念网络模型和适用于具体场景的贝叶斯信念网络算法。 - Considering the factor of alarm loss, a symptom node layer is added to the improved bipartite graph model and a network fault propagation model using the three-layer belief network is proposed.
考虑了告警丢失因素，在改进的二分图模型中加入了隐含的症状节点层，提出了基于三层因果图的网络故障传播模型。 - In the aspect of the network fault diagnosis, we study the fast network fault diagnose with the application of the Bayesian Belief Network.
在网络故障诊断方面，本文采用贝叶斯置信网，研究了网络故障的快速发现问题。 - Considering the features of business information and effect of relationship among index words to retrieval performance, this model extends the belief network with four layers of nodes, and applies similarity thesaurus to expand the user query and describe the relationship among index words.
考虑货源信息的特征和标引词之间的相互关系对检索结果的影响，该模型采用四层节点的信任度网络模型，应用相似性叙词表扩展用户查询和描述标引词之间的关系。 - Dynamic Causality Diagram has some advantages compared with Belief Network, it is more convenience to represent causal relationship, and the superiority is taken on especially in the Fault Diagnosing field.
但因果图与信度网相比又具有一些自己独特的优点，在不确定性知识间的因果关系表达更加方便，尤其在故障诊断领域更有独特优势。