To improve system's robustness, uncertain reasoning based on certainty factor is introduced.
为了提高系统的鲁棒性，采用了基于可信度因子的不精确推理机制。
Uncertain reasoning and decision-making is used to fuse the data in the different space and time fields.
最后根据不确定推理与决策理论对不同空域和时域的数据进行融合。
In the end this paper gave a assumption that we can simulate the human's geist by implementing the uncertain reasoning process.
最后提出了通过实现推理过程不确定性来模拟人类感性的设想。
Using uncertain reasoning, a reasoning model and an algorithm are presented, which give the answer to this problem effectively.
本文利用不确定推理中的概率推理方法，设计了购买决策树回溯推理的模型和算法，有效解决了这一问题。
Probabilistic logic makes use of the method of logic reasoning to deal with the uncertain reasoning, which is cause by randomicity.
概率逻辑是用逻辑推理的方法解决因随机性引起的不确定性推理问题。
The idea and arithmetical method may be generalized to deal with a variety of problems for the uncertain reasoning decision-making.
其思想和算法可推广应用到其它各种不确定性推理决策问题中去。
In order to cater to the demand of objective problems, the study of uncertain reasoning is needed in the artificial intelligence areas.
为此，人工智能需要研究不确定性推理方法，以满足客观问题的需求。
The lossless decomposition of compound T rules is explored in detail. A new algorithm dealing with uncertain reasoning Problems is Presented at last.
对复合三值规则的无损分解进行了详细探讨，最后提出了一个能进行不确定推理的新算法。
In the paper, an uncertain reasoning method based on topological transformation is constructed by means of fuzzy topology and fuzzy mathematics theory.
本文用模糊拓扑和模糊数学的方法给出了一种基于拓扑变换的不确定性推理方法。
The methods of real time reasoning and uncertain reasoning are also described. In the end, a simulation instance is analyzed to express the application of ECSS.
简介ECSS的主要特点和工作原理，着重叙述了ECSS的实时推理和不确定推理方法，并以仿真实例说明ECSS 的应用。
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.
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。
The fundamental tools of A.I. shifted from Logic to Probability in the late 1980s, and fundamental progress in the theory of uncertain reasoning underlies many of the recent practical advances.
研究人工智能的基础工具在80年代后期从逻辑转向了概率，而关于不确定性的理论研究的进展成为了近期许多应用的基础。
The fundamental tools of A. I. shifted from Logic to Probability in the late 1980s, and fundamental progress in the theory of uncertain reasoning underlies many of the recent practical advances.
研究人工智能的基础工具在80年代后期从逻辑转向了概率，而关于不确定性的理论研究的进展成为了近期许多应用的基础。
Bayesian network is one of the most efficient models in the uncertain knowledge and reasoning field.
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。
The main issues addressed are uncertain knowledge representation and approximate reasoning based on fuzzy set theory.
本文主要探讨了基于模糊集合理论的不确定知识表示和近似推理方法。
Three experiments with participants of college students were done to investigate feature reasoning in uncertain categorization in the concentrative presentation of samples of category members.
用大学生被试，通过三个实验探讨在集中呈现类别成员样本信息的归类不确定情景下的特征推理。
Fuzzy sets and fuzzy logic are important mathematical tools for processing uncertain and vague information, which has been widely applied to approximate reasoning and so on.
模糊集与模糊逻辑是处理大量存在的不确定性与模糊性信息的重要数学工具，在近似推理等领域有着广泛的应用。
This article proposes a data sorting method via the EM algorithm, for the purpose of mining high-quality decisions by performing data reasoning in a database with incomplete, noisy and uncertain data.
针对存在不完整、含噪声和不确定数据的数据库，通过挖掘高质量的决策，对数据库的数据进行推理，提出了一种基于EM算法的数据清理方法。
The reasoning mechanism of PTES can deal with both uncertain facts and uncertain rules in a formal way by employing possibilistic logic and fuzzy set theory as its logical basis.
PTES的推理机制使用了可能性逻辑及模糊集合理论作为其逻辑基础，并以一种形式化的方法提供了处理非确定事实及非确定规则的能力。
Group reasoning based on rough sets-combining uncertain information deployment method with group decision theory and method, is a new kind research area.
基于粗糙集理论的群体推理——即将不确定性信息处理技术与群决策理论与方法集成的研究，是一个崭新的研究领域。
In this ameliorative model, uncertain information has an effect on accuracy of reasoning conclusion. As a result, reliability of reasoning conclusion is improved.
在该模型中，不确定信息作用在推理结论的正确度上，提高了结论的可靠性。
This paper introduces the mathematics foundation of Subjective Bayes Method, describes application of reasoning under uncertainties and provides two ways to solve the uncertain question.
介绍主观贝叶斯方法数学理论，描述其在不确定性推理中的应用，给出两种求解方法。
This paper introduces the mathematics foundation of Subjective Bayes Method, describes application of reasoning under uncertainties and provides two ways to solve the uncertain question.
介绍主观贝叶斯方法数学理论，描述其在不确定性推理中的应用，给出两种求解方法。
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