So the ability of resolving the uncertain problems represents the intelligence of system , and the reasoning model based on uncertainty has become a key research project in ai and expert system ( es ) . uncertainty knowledge representation can be classified into two categories : probabilistic and non - probabilistic 不确定知识表达的方法可分为两大类：一类是基于概率的方法，包括信度网( beliefnetwork ) 、动态因果图( dynamiccausalitydiagrams ) 、马尔可夫网( markovnetwork )以及在专家系统prospector中使用的方法等。
Dynamic causality diagram was first proposed by professor zhang qin in 1994 , it is a mathematics tool combined with probability and graph theory , just like the belief network , its characteristic is to provide the method of uncertain knowledge representation and agility reasoning , it adopts nodes to represent random variables in the domain and directional edges between nodes to represent causal relationship between variables , linkage intensity to represent the strength of the link between these variables , it supports the forms of reasoning from cause to effect and from effect to cause and together 动态因果图由张勤教授1994年提出,它与信度网类似,是概率论与图论结合的一种数学工具,其特点是提供不确定知识的表达和灵活的推理方法:用节点表示事件或变量,有向边表示因果关系,并用连接强度来表示因果关系的强度,支持由原因到结果的正向推理方式和由结果到原因的反向推理方式以及正反向混合推理方式。
The theory , which is found on and brought forward by pro . qin zhang is the causality trees / diagram ' s knowledge representation methodology and calculating theory based on probability . the research bases itself upon building own knowledge right for our country in ai software and changing the situation which we just follow the outside research in ai 本项研究基于张勤教授所提出的因果图的概率知识表达方式和推理计算原理，立足于建立具有我国自主知识产权和特色的不确定知识表达和推理的理论模型和工具，发展具有我国自主知识产权的人工智能软件产业，改变我国在人工智能领域跟踪国外研究的状况。
Rough set theory is a soft compulation tool to solve the inaccurate and uncertain information proposed by z . pawlak in 1980 ' s , while with the rapid development of internet and electronic books , text mining is an important research field . this article carries on in - depth research to text mining based on rough set theory 粗糙集理论是二十世纪八十年代由z . pawlak提出的一种新的处理不精确、不确定知识的软计算工具，而文本挖掘技术是随着互联网的蓬勃发展和电子图书的出现逐渐形成的信息技术领域的一个重要的研究方向，本文对基于粗糙集理论的文本挖掘进行了较为深入的研究。
* the belief network modeling of telecommunication network congestion the belief network is a mathematical tool based on both the probability and graph theory , which gives us an effective approach to represent uncertain knowledge and do flexible inference . it has been hot research topic in diagnosis , decision theory , ai , data mining and so on 综合起来，主要研究了以下几方面的内容： *电信网阻塞的信度网模型信度网是概率论与图论完美结合的一种数学工具，其特点是提供不确定知识的表达和灵活的推理方法，在故障诊断、决策理论、人工智能、数据挖掘等方面成为研究热点。
