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。
Bayesian Networks is a model that efficiently represents knowledge and probabilistic inference and is a popular graphics decision-making analysis tool.
贝叶斯网络是目前不确定知识和推理领域最有效的理论模型之一。
Bayesian network is one of the most efficient models in the uncertain knowledge and reasoning field.
以特征信息结构树为基础，对贝叶斯网络模型进行推理，来获得客户需求的兴趣集中点。
Through reasoning Bayesian network model based on the features information construction tree of client requirement, the client requirement concentration is acquired.
为了实现过程状态模型的智能输出，运用人工神经网络实现自动推理的功能；
In order to achieve intelligent process state model output, the use of artificial neural networks for automatic reasoning capabilities.
在研究现有文本信息检索技术的基础上，设计了基于推理网络的文本检索模型。
By the research on the existent IR (Information retrieval) technology, a text retrieval model based on inference network is designed.
研究了模糊推理神经网络计算模型及其连续函数逼近能力。
This paper deals with the computational model for fuzzy reasoning neural network and its function approximation capability.
提出一种基于步态规划分级结构的自适应网络模糊推理系统控制策略，该方法不需要确定双足机器人运动学和动力学模型。
Proposed an adaptive network fuzzy inference system control strategy based on hierarchy structure of gait planning, which do not require detailed kinematics or dynamic biped models.
提出一种基于因果网络的诊断推理模型。
A diagnostic reasoning mode based on causal network is proposed.
分析了网络安全态势估计问题的本质特征，构造了网络安全态势推理评估的求解模型。
Analyzing the essential characteristic of the network security situation assessment, and the reasoning model is proposed.
本文在向量空间模型和概率推理网络的基础上提出了一个基于关键词与概念相结合的混合信息检索模型。
We bring forward a hybrid model that is based on a combination of keywords and concept. The hybrid model is built on vector space model and probabilistic reasoning network.
应用模糊控制的逻辑推理性能，借助神经网络的学习能力，提出了一种模糊神经网络预测控制模型。
A fuzzy neural network prediction control model is stated by using the logic inference performance of fuzzy control and the learning ability of neural network.
针对目标综合识别过程中的复杂性和不确定性特点，利用贝叶斯网络融合模型对融合识别过程进行概率建模及推理。
For dealing with the complexity and uncertainty in the target identification fusion, the fusion model of Bayesian Networks is used.
模糊推理网络(FIN)和模糊联想记忆网络(FAM)是两种最重要的FNN模型。
Fuzzy inference network (FIN) and fuzzy associative memory network (FAM) are two most important FNN models.
利用汽车发动机点火系统的故障实例验证了基于BP模型的神经网络故障诊断正向推理方法的有效性和可行性。
The validity and feasibility of the forward reasoning method for fault diagnosis based on BP neural networks are verified by the example of the faults in the ignition system of automobile engine.
该模型在传统专家系统基础上，增加了神经网络集成模块，以解决知识的自动获取和推理问题。
Based on the traditional expert system, the integrated module of neural network ensembles is applied in this model in order to insure the automatic acquisition of knowledge and reasoning.
采用模糊神经网络方法进行磨削加工尺寸精度的控制，给出了模糊推理BP网络模型。
In the paper, fuzzy neural network method is used to control the size accuracy in grinding process and fuzzy inference BP-network model is produced.
研究了基于贝叶斯网络的推理模型以及基于此模型的推理算法。
The inference model based on Bayesian Network is discussed and the algorithm based on the model is presented.
第二章详细介绍了基于本体论的语义网络模型理论，包括语义网络模型的结构、知识表示及推理机制。
Thesecond chapter introduced semantic network model theory in detail based on ontology, including model structure, knowledge expression and inferential mechanism.
本文主要涉及的不确定推理模型包括主观贝叶斯的概率推理模型，可信度理论推理模型，证据理论及其改进推理模型以及神经网络推理模型。
In the paper, the models of uncertain reasoning are focused, such as the reasoning model of Bayes probability, Reliability theory, D-S evidence theory and Neural Network.
但直接将该模型用于语音识别，将会使网络产生规则灾和网络推理失效等问题。
But if this model is applied in speech recognition directly, it would produce the problems of rule disaster and network ratiocination invalidation.
该推理模型前级采用神经网络并行子网，用于目标的预分类，后级采用证据理论用于多周期的不确定性推理和概率的全局分配。
The forestage of the fusion model completes target presort and its post-stage is used to multi-period uncertainty inference and the whole set distribution of probability.
集成神经网络模型以故障层次模型为参考，可以大大缩小诊断推理的求解空间，最终快速定位发生故障的根本部位。
Refer to hierarchical fault model, the integrated ANN diagnostic model can contract the scope of diagnostic reasoning, and find quickly the fault components.
对配电网的空间负荷预测方法进行改进，重点研究小区用地分析的模糊推理模型，把人工神经网络技术与模糊推理系统相结合的方法应用于小区用地分析。
This paper presents the improvement of spatial load forecasting method of distribution network, and the fuzzy inference on small area land-use analysis is emphatically studied.
设计了一个简单的人工智能故障诊断系统模型，它包括知识库、模糊推理、神经网络和控制模块等。
A simple artificial intelligence system for fault diagnosis established in this paper. The system consists of knowledge base, fuzzy reasoning module, neural network module and control module.
在提出广义模糊推理概念的基础上，提出并分析了广义模糊径向基(rbf)神经网络模型，给出了该网络的广义学习算法。
A new concept of generalized fuzzy inference and the generalized fuzzy RBF network model are presented. The generalized Lear ni ng algorithm of this network model is derived.
文章提出了毛纺织工艺设计智能化模型，通过基于案例(CBR)和基于规则的推理(rbr)以及人工神经网络(ANN)等关键技术的引入，提高了系统解决实际问题的能力。
This paper presents the wool textile process intelligent design model (WTPIDM), by the introduction of CBR, RBR, ANN technologies, improving the system capability to solve the problems.
提出了基于知识的毛纺产品工艺设计智能模型，通过基于案例（C BR）和基于规则的推理（RBR）以及人工神经网络（ANN）等关键技术的引入，提高了系统解决实际问题的能力。
This paper presents the wool textile process intelligent design model(WTPIDM), by the introduction of CBR, RBR, ANN technologies, improving the system capability to solve the problems.
利用汽车发动机点火系统的故障实例验证了基于BP模型的神经网络故障诊断正向推理方法的有效性和可行性。
The validity and feasibility of the forward reasoning method for fault diagnosis based on BP neural networks are verified by the example of…
借助于辨识的过量空气系数自适应神经网络模糊推理系统(ANFIS)模型，进行了静态空燃比前馈控制仿真。
By means of an identified adaptive neural fuzzy inference system (ANFIS) model of the excess air factor, the simulation of static state air fuel ratio feed-forward control was carried out.
借助于辨识的过量空气系数自适应神经网络模糊推理系统(ANFIS)模型，进行了静态空燃比前馈控制仿真。
By means of an identified adaptive neural fuzzy inference system (ANFIS) model of the excess air factor, the simulation of static state air fuel ratio feed-forward control was carried out.
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