专家系统的实时性分析

在一些复杂控制系统中 ,专家系统作为一个决策控制器 ,满足整个系统的性能需要 ,因此研究专家系统的推理时间是必要的。专家系统的推理时间与其推理模式、知识库结构等因素有关。针对知识库结构 ,通过专家系统的推理时间研究了实时性问题 ,利用时间齐次马尔可夫链为专家系统知识库进行建模 ,并给出了相应的时间估计模型及其排列准则。     

专家系统的实时性分析

在一些复杂控制系统中,专家系统作为一个决策控制器,满足整个系统的性能需要,因此研究专家系统的推理时间是必要的。专家系统的推理时间与其推理模式、知识库结构等因素有关。针对知识库结构,通过专家系统的推理时间研究了实时性问题,利用时间齐次马尔可夫链为专家系统知识库进行建模,并给出了相应的时间估计模型及其排列准则。     

一种基于任务分解的多知识库协同求解专家系统

针对特定领域的知识特点、知识表示方法及采用的推理模型,提出一种基于产生式规则的多知识库专家系统.该系统改进传统专家系统的框架设计,根据求解问题的类别划分将知识库分解成相应的子知识库,再将子知识库的知识规则按知识表示的深度加以分解,建立反映专家经验知识的浅层知识库和原理性知识的深层知识库.系统采用主推理机和从推理机二级推理方式,不同的子知识库采用相应的从推理机.从而任务单一,搜索范围减小,能快速形成待检目标集.主从推理机制与正反向推理结合,提高系统的推理效率.运用该系统模型建造的农业领域专家系统实例,运行效率得到改善,速度显著提高.     

液压系统故障诊断专家系统

介绍了液压系统故障诊断专家系统的基本结构及其开发的基本方法,重点介绍了人机接口、知识库的建立以及推理机制的构成。     

故障诊断专家系统知识库编辑和维护系统

设计了一种适用于故障诊断专家系统知识库编辑和维护系统。该系统从设备结构出发,将深知识和浅知识统一为一种形式,分别建立关于系统的部件、状态、属性、关系等字典,利用这些字典分别建立系统的结构知识库和推理知识库。还对系统的实现和功能进行了说明。     

远程液压专家系统的研制

根据工程机械液压系统工况特点，设计了远程液压专家系统。介绍了专家系统的总体结构，并着重论述了该专家系统的知识库的构成及其内部的推理机制。系统利用了Web数据库及网页编程的技术特点，充分发挥Internet收集、共享知识和数据的优势，改善了诊断专家系统的性能和扩展增强了系统的诊断功能。在专家系统的内部推理机制上利用了专家系统的正向推理及深度优先的搜索方式。将系统运用到某工程机械的摊铺机液压系统的故障诊断中，收到了很好的效果。     

基于ASP.NET的甘肃省玉米病虫害诊断专家系统知识库构建

知识库是专家系统的核心模块之一,知识库中知识表示方法和结构的不同,直接影响专家系统的工作效率、推理机制、求解策略及系统的适用性。该文分析了专家系统的体系结构,采用"Web浏览器/Web服务器/数据库"三层分布的工作模式,详细阐述了玉米病、虫害实体的E-R模型,用SQL Server 2005构建玉米病虫害知识库、知识获取以及知识表示技术,在专家系统领域具有一定的借鉴作用,促进了农业知识的普及。     

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。     

专家系统在钢铁质量检验判定中的应用研究

运用专家系统功能及结构和知识推理控制策略,对钢铁质量检验判定专家系统的建立包括知识库的建立、推理过程和解释机制等进行深入的探讨与研究。     

裁断机实时监控与故障诊断专家系统

针对轮胎帘布裁断机监控系统功能单一、集成化和智能化程序低的现状,采用虚拟仪器开发平台LabVIEW,在IPC+PLC硬件架构上开发了实时EtherNet/IP工业以太网通信的监控与故障诊断专家系统.通过故障树分析,建立裁断机故障树模型并计算最小割集以及相应重要度,建立了专家系统知识库,解决了专家系统知识库获取难的问题.基于故障树割集重要度的推理机推理过程简洁直观,灵活通用.设计的裁断机监控系统交互界面简明清晰,故障诊断快速准确,在厂测试和设备交付后的反馈情况表明,系统能有效缩短设备故障停机检修时间,提高了设备利用率.     

一种面向对象的模糊知识库模型

本文给出了一种专家系统模糊知识库的结构模型。重点讨论了该模型的体系结构和采用面向对象技术表示模糊规则的方法。并介绍了采用面向对象方法分析和设计模糊知识库的技术和采用面向对象串行化技术实现模糊知识库持久保存的方法。最后,分析了采用面向对象技术构建模糊知识库的优点。     

Building knowledge base management systems

Advanced applications in fields such as CAD, software engineering, real-time process control, corporate repositories and digital libraries require the construction, efficient access and management of large, shared knowledge bases. Such knowledge bases cannot be built using existing tools such as expert system shells, because these do not scale up, nor can they be built in terms of existing database technology, because such technology does not support the rich representational structure and inference mechanisms required for knowledge-based systems. This paper proposes a generic architecture for a knowledge base management system intended for such applications. The architecture assumes an object-oriented knowledge representation language with an assertional sublanguage used to express constraints and rules. It also provides for general-purpose deductive inference and special-purpose temporal reasoning. Results reported in the paper address several knowledge base management issues. For storage management, a new method is proposed for generating a logical schema for a given knowledge base. Query processing algorithms are offered for semantic and physical query optimization, along with an enhanced cost model for query cost estimation. On concurrency control, the paper describes a novel concurrency control policy which takes advantage of knowledge base structure and is shown to outperform two-phase locking for highly structured knowledge bases and update-intensive transactions. Finally, algorithms for compilation and efficient processing of constraints and rules during knowledge base operations are described. The paper describes original results, including novel data structures and algorithms, as well as preliminary performance evaluation data. Based on these results, we conclude that knowledge base management systems which can accommodate large knowledge bases are feasible. Edited by Gunter Schlageter and H.-J. Schek. Received May 19, 1994 / Revised May 26, 1995 / Accepted September 18, 1995     

A hierarchical expert system for computer process control

This paper reports on the design and implementation of an expert system for computer process control (HESCPC). The complexity of the expertise necessary for computer process control applications requires that the expert system architecture be structured into a hierarchy of classes of specialized experts. The architecture of HESCPC integrates four classes of expert systems: operator/manager companion expert class, control system algorithm design expert class, hardware expert class, and software expert class. The paper is concerned with the design and implementation of the general system architecture, an operator adviser expert for a nuclear power plant and a control system designer expert using a state space feedback approach. Although the design and implementation aspects of all experts are discussed, the emphasis is on the latter.

At this stage of the HESCPC development, the declarative knowledge represented by 423 metarules and 1261 rules is distributed on a hierarchical structure among 20 experts on different levels of the hierarchy which are able to communicate among themselves to solve difficult control problems.

Examples of control system design sessions of linear mono and multivariable systems using feedback state space approach are given. A run time of an operator-adviser data-driven expert system for a nuclear plant is also presented.     

An object-based architecture for biomedical expert database systems

Objects play a major role in both database and artificial intelligence research. In this paper, we present a novel architecture for expert database systems that introduces an object-based interface between relational databases and expert systems. We exploit a semantic model of the database structure to map relations automatically into object templates, where each template can be a complex combination of join and projection operations. Moreover, we arrange the templates into object networks that represent different views of the same database. Separate processes instantiate those templates using data from the base relations, cache the resulting instances in main memory, navigate through a given network's objects, and update the database according to changes made at the object layer. In the context of an immunologic-research application, we demonstrate the capabilities of a prototype implementation of the architecture. The resulting model provides enhanced tools for database structuring and manipulation. In addition, this architecture supports efficient bidirectional communication between database and expert systems through the shared object layer.     

线性控制系统计算机辅助设计的专家系统

本文研究并实现了用于进行控制系统的计算机辅助分析和设计的专家系统.介绍作者提 出的一种新的分层的专家系统总体结构.该系统为控制问题在计算机中的描述提供了一个良 好而统一的方法.具有运用和处理控制领域中知识和经验的能力;问题求解的机制中有语义 回溯能力;对知识库有编辑能力等.简要介绍系统的三种工作模式和体现系统智能水平之一 的两级知识库.该系统已在IBM-PC/AT和COMPAQ-386等机器上运行.     

Towards knowledge-based infolog specifications A case study of information engineering

A radically new approach to computing, the so-called knowledge-based information processing is achieving striking success in supporting activities needing logical power, human judgement, reasoning and expertise. It offers universal applicability for problem-solving, in particular in more complex tasks than those presently handled by computer systems. The current state of the art and future prospects for the development of a computer system which either performs expert tasks automatically or is used interactively by experts to increase their productivity are reviewed. The weak points we need to look at, namely the lack of guidelines for building such systems, and some dead ends are indicated. Some new results are expected by applying this key technology to our case study, the construction of a Systems Specification Support System (S4). Its knowledge base written in PROLOG captures and encodes human expertise about the INFOLOG model and INFOLOG specifications, which is made available via consultation to formulate specifications and, possibly, advice. The architecture of the knowledge base is presented by discussing its abstraction levels. This investigation provides also a methodology in structuring a systems analyst's knowledge about an application. This means how to find out the main kinds of objects, including their relationships, in some problem domain.     

Expert System Hardware for Fault Detection

This paper focuses upon the development of three new electronic architectures of inference engines as a part of a hardware expert system applied to very high-speed faults detection in industrial processes. The architecture of this expert system consists of an inference engine (a dedicated processor that is necessary due to the high-speed requirements and the repetitiveness of the operation), which uses a pattern-directed inference system; a fact base, which stores the status of the signals at each moment, and a static knowledge base, which contains the inference rules compiled from expert knowledge. A circuit for analyzing time is also presented. This allows time to be taken as another variable of the process and carries out a redundancy analysis simultaneously with the fault detection module.     

INTEGRATED KNOWLEDGE ACQUISITION FROM TEXT,PREVIOUSLY SOLVED CASES,AND EXPERT MEMORIES

Within the model-based knowledge engineering framework, an integrated knowledge acquisition method was developed for a complex real-world domain with different traces of expertise. By having an expert constructively explain the previously solved cases with more general information from other traces of expertise ( text, expert memories) a model-centered knowledge base is constructed. The proposed method allows for an early knowledge verification where the relevance, sufficiency, redundancy, and consistency of knowledge are already assessed at an informal level The early knowledge verification efficiently prepares the consecutive knowledge formalization. Through a cognitively adequate model of expertise and the explanation-oriented knowledge elicitation procedures, user-friendly second-generation expert systems may be developed.     

Applying systems analysis techniques to knowledge engineering

Abstract: This paper deals with the issue of knowledge elicitation for expert systems. Specifically, it looks at the requirements of the knowledge elicitation process and the suitability of structured methods from systems analysis to carry out part of the elicitation task. The techniques of data flow analysis, entity-relationship analysis and entity-life cycle analysis are used to structure the data associated with the expert task. The methods proposed lay emphasis on the definition of limited data sets at the boundary of the explicit knowledge base and the identification of status attributes to model the control of activation of 'processes' within the knowledge base. Attention is also paid to the relationship between the resulting logical model, and two popular methods of knowledge representation, namely, Production Systems and Frames.