一个可处理不确定性知识的专家系统开发工具

介绍了用面向对象的可视化语言Ｖｉｓｕａｌ Ｃ＋＋实现的一个可处理不确定性知识的专家系统开发工具ＲＥＳＴＯＯＬ,着重描述了其知识库组织、不精确推理机的实现及推进过程可视化,并给出了一个运行实例。     

搅拌器选型专家系统的知识处理和系统实现

从知识获取,知识表达,采用模糊集理论处理领域中不确定性知识以及群组决策等方面,阐述了搅拌器选型专家系统知识处理的解决方案。由系统结构和操作过程,对整个专家系统如何实现进行了描述。     

专家系统中基于粗集的知识获取、更新与推理

知识获取、知识更新和不确定性推理是设计专家系统的重要方面。根据粗集理论，提出了一种专家系统的结构模型，该系统在规则获取的基础上，利用系统运行的实例增量式地更新知识库中的规则及其参数，以改善系统的性能，利用知识库中的规则及数量参数进行不确定性推理，得出结论的可信度。     

基于CAN总线的雷达装备BIT故障诊断专家系统研究

介绍了一种基于CAN总线的分散检测,集中诊断、显示的雷达BIT故障诊断系统,描述了其硬件组成、专家系统结构,知识表示和推理机制。通过在该雷达BIT中采用专家系统诊断方法,使得推理机与知识库分离,便于诊断知识库的扩充、维护,有效提高了系统BIT故障诊断能力。     

证据推理的理论基础和实现技术

利用证据理论作为不确定知识的表示和处理框架,正在成为专家系统不确定推理模型的研究热点。作为基础,本文给出了证据理论中不确定性的基本测度及其性质、证据组合规则和基本概率赋值函数的计算方法;根据专家系统知识库的结构,本文讨论了平坦化及层次化假设空间上证据推理的实现技术。     

基于本体的故障诊断知识库系统的构建

传统故障诊断技术采用专家系统的知识库是封闭的或半封闭的,其知识库的构造和知识的输入与修改均需由设计者来进行,不能从故障诊断的成功经验中提取相关的知识。本体作为知识的基本元素,可以进行知识类比推理,抽象出事物内在的本质,适合于描述知识库的内部单元。提出一种基于本体的故障诊断知识库系统模型,并依据该模型设计了故障诊断专家系统。     

智能型财务报表分析专家系统的设计与实现

传统的财务报表分析专家系统运作模式存在过于僵化、缺乏弹性与自我学习能力、产生的结果难以涵盖所有情况等问题,针对以上问题对传统的财务报表分析专家系统进行改进,在知识表达方式上采用框架式以及本体论知识表达法取代传统的规则式知识表达法;知识框架规则采用模糊逻辑表达式,有效处理决策环境中的不确定性;在知识库完整性方面增加了知识库扩充机制。介绍了系统的设计思想和实现机制,对系统进行了绩效评估和知识库评估,验证了在导入模糊逻辑以及本体论后,能够有效地增加系统执行效率,降低知识库建立与维护的复杂度。     

故障诊断专家系统中知识库组织和维护技术的研究

在开发化工过程实时故障诊断专家系统的基础上,本文讨论了知识库的组织和维护技术,对知识表示和知识库结构进行了详细介绍。在知识库维护方面,采用面向对象的方法描述领域知识,并实现知识获取和转换；对于知识校验,提出一种基于有向图的知识校验方法。以润滑油生产过程为例,讨论了系统的知识校验过程。本文讨论的技术和策略已应用于润滑油过程实时故障诊断专家系统。实际应用表明,该技术和策略保证了知识库和专家系统的稳定和高效率。     

初中几何专家系统中的知识获取及实现

描述了初中几何专家系统中知识获取及实现的一般过程,指出了知识获取及实现中的难点和重点。由于研究问题的复杂性,专家系统规则库中规则量往往十分庞大,这给规则库的管理和维护带来很大不便。专家系统知识库的冗余性是影响系统运行效率和知识库维护的一个重要方面,针对一个具体的专家系统——平面几何智能解题系统,分析了关于知识库规则生成时效率低的问题,然后利用基于粗糙集的约简理论来消除和减少规则库的冗余,使得系统规则库中的规则精炼、简洁,易于维护,同时大大提高了系统的效率。     

初中几何专家系统中的知识获取及实现

描述了初中几何专家系统中知识获取及实现的一般过程,指出了知识获取及实现中的难点和重点.由于研究问题的复杂性,专家系统规则库中规则量往往十分庞大,这给规则库的管理和维护带来很大不便.专家系统知识库的冗余性是影响系统运行效率和知识库维护的一个重要方面,针对一个具体的专家系统--平面几何智能解题系统,分析了关于知识库规则生成时效率低的问题,然后利用基于粗糙集的约简理论来消除和减少规则库的冗余,使得系统规则库中的规则精炼、简洁,易于维护,同时大大提高了系统的效率.     

A knowledge-based support system for mechanical ventilation of the lungs. The KUSIVAR concept and prototype

The KUSIVAR is an expert system for mechanical ventilation of adult patients suffering from respiratory insufficiency. Its main objective is to provide guidance in respirator management. The knowledge base includes both qualitative, rule-based knowledge and quantitative knowledge expressed in the form of mathematical models (expert control) which is used for prediction of arterial gas tensions and optimization purposes. The system is data driven and uses a forward chaining mechanism for rule invocation. The interaction with the user will be performed in advisory, critiquing, semi-automatic and automatic modes. The system is at present in an advanced prototype stage. Prototyping is performed using KEE (Knowledge Engineering Environment) on a Sperry Explorer workstation. For further development and clinical use the expert system will be downloaded to an advanced PC. The system is intended to support therapy with a Siemens-Elema Servoventilator 900 C.     

Statistical consultation — Who's the expert?

A survey is given of requirements an expert system must satisfy to be usable in disciplines other than pure statistics. Relevant data were gathered during a three year observation of consultations between researchers and medical statisticians. It had been anticipated that a knowledge base of limited size could be established and a set of largely deterministic rules could be identified which would enable the knowledge to be harnessed as an informative and utilitarian backward chaining expert system.     

基于证据理论的不确定性推理方法及其应用

针对民航无线电管理中遇到的干扰问题以及客观世界中描述客观现象的知识和信息具有不确定性的特点,结合民航无线电干扰查处的实际情况,提出基于一种产生式规则的知识表示方法,以区间确定因子描述不确定性。提出基于Dempster-Shafer证据理论和区间确定因子的不确定性推理方法。进一步根据领域专家经验建立民航无线电干扰查处规则,以基于Dempster-Shafer证据理论和区间确定因子的不确定性推理方法为推理机,给出民航无线电干扰查处专家系统的结构及工作流程,采用C#语言结合MySQL数据库开发民航无线电干扰查处专家系统,并通过案例分析说明该系统的有效性和实用性。     

Support logic programming

This article describes a support logic programming system which uses a theory of support pairs to model various forms of uncertainty. It should find application to designing expert systems and is of a query language type like Prolog. Uncertainty associated with facts and rules is represented by a pair of supports and uses ideas from Zadeh's fuzzy set theory and Shafer's evidence theory. A calculus is derived for such a system and various models of interpretation given. the article provides a form of knowledge representation and inference under uncertainty suitable for expert systems and a closed world assumption is not assumed. Facts not in the knowledge base are uncertain rather than assumed to be false.     

Constructing and consulting the knowledge base of an expert systems shell

Abstract: This paper presents an expert system shell whose inference mechanism uses backward chaining. In particular the modules devoted to constructing and consulting the knowledge base are illustrated. The programming environment is based on the Arity-Prolog language, a popular Prolog dialect running on IBM PCs and compatibles.     

电机自动装配线故障诊断模糊专家系统

为了对电机自动装配线上的故障进行正确有效的诊断，基于其工艺流程，运用模糊逻辑与专家系统知识，利用Visual C 以及Visual Foxpro作为编程工具，作者开发了用于装配线的故障诊断模糊专家系统（简称FES），该系统包括用户接口，知识库，推进机和历史记录数据库，采取模糊前向基于规则推理策略，并能根据可信度预测故障严重性。     

Fuzzy expert system with double knowledge base for ultrasonic classification

This article shows a pattern recognition method for object classification using ultrasonic sensors and a dual knowledge base fuzzy expert system. The developed system uses a pair of ultrasonic sensors for obtaining information about the object shape from the ultrasonic echo signal envelope. In order to reduce the size of the database, a set of parameters is calculated for extracting knowledge about the object. However, the information provided by ultrasonic sensors contains a very high uncertainty level. This uncertainty is caused by several environmental effects, which are very difficult to eliminate in industrial applications. Among these environment factors are the air temperature and humidity, the air movement, etc. They create variations in the proprieties of the medium and disturbances during the acoustic propagation process. The presented system has been specially designed for industrial applications, where it is very difficult to reduce these disturbances and where it is necessary to use intelligent systems with high autonomy. The fuzzy expert system proposed has a dual knowledge base, that is, a statistical knowledge located on the memberships functions, and the standard rule-based knowledge. This expert system deals with the uncertainties in the information, and it is able to generate and modify the knowledge base and the decision rules in an automatic way. Furthermore, it is able to adapt the knowledge base to the slow changes produced by disturbing factors, such as humidity and temperature. On the other hand, because this system maintains a rule-based structure it is very easy to incorporate expert human knowledge.     

基于数据库的专家系统设计

该系统属于基于规则的产生式系统,系统采用关系模式来描述知识库,用数据库方法存储管理知识库,以改善知识库的性能,克服专家系统不能有效地利用现有知识库的局限。该系统由以下几部分组成:诊断模块,咨询模块,分析模块和帮助模块等。同时,还建立了咨询知识库和缺陷图形库。为将来对系统的进一步开发打下了良好的基础。     

VALIDATION OF FIRST-ORDER RULE-BASED SYSTEMS1

Knowledge base validation and knowledge base refinement aim to help the expert to improve an existing knowledge base. They deal with the final knowledge acquisition phase and rely on a quality measurement of an existing knowledge base. We present our approach to knowledge base refinement, which is based on results in the domain of knowledge base validation. Our approach is based on a general consistency definition of a knowledge base and on a study of causes of knowledge base inconsistency. Our approach relies significantly on a differentiation of sure and expert knowledge in the knowledge base. We have implemented a system that has two phases: one computational phase decides on the consistency of a knowledge base, and, if necessary, a second phase helps the expert to interactively update the knowledge base. We present some related work in the domain. We illustrate the use of our system with an example.