汽轮发电机组故障诊断专家系统的研究

建立一个基于知识的汽轮发电机组故障诊断专家系统ＫＢＦＤＥＳ，该系统采用“框架＋规则”知识表示技术，并将框架驻留在内存，而将规则驻留在虚拟盘上；在诊断过程中采用广义的不精确推理策略，并对重要信息用一个组合神经网络进行智能识别；系统将神经网络技术和ＩＤ３算法结合，可以实现从诊断实例自动获取知识。     

LOTUS NOTES数据库中的主动推出式多媒体播发技术

本文讨论如何在ＬＯＴＵＳ ＮＯＴＥＳ数据库中实现主动推出式多媒体播发技术，从而通过浏鉴器文档的主动推出式播发，其中涉及的技术有ＣＧＩ、ＬＯＴＵＳ ＮＯＴＥＳ ＨＩＴＥＳＴ ＡＰＩ等，使得该播发技术具有文档自动切换、多媒体播发、自动滚屏等功能。     

汽轮发电机组故障诊断专家系统的研究与应用

介绍一个基于知识的汽轮发电机组故障诊断专家系统ＫＢＦＤＥＳ，系统采用“框架＋规则”知识表示技术，并将框架驻留在内存，而将规则驻留在虚拟盘上；在诊断过程中采用广义的不精确推理策略，并对重要信息用一个组合神经网络进行智能识别；系统将神经网络技术和ＩＤ３算法结合可以实现从诊断实例自动获取知识。     

基于产生式的多语言程序理解的算法

提出一种程序理解实现方案,通过将程序设计语言的词法规则和语法规则以产生式表示,设计基于产生式多语言程序处理算法,将产生式自动转化为对应的词法和语法规则函数,使得不同的程序设计语言规则可以采用统一的方式描述,从而可用一套程序理解系统实现对多种程序设计语言的程序理解,以后增加某种程序设计语言的程序理解,只要定义对应程序设计语言的词法和语法规则产生式即可实现,有效地解决了程序理解系统的共享性难题。     

基于OSI的CIMS网络管理信息库的与实现

本文根据ＯＳＩ的管理框架提出了一种面向ＣＩＭＳ网络管理的管理信息库的实现结构，它包括使用含树的概念来表示管理信息，利用ＯＳＩ的ＣＭＩＳ来控制对ＭＩＢ的访问，使用文件系统来存放管理信息，文章还介绍了ＭＩＢ实现结构在Ｕｎｉｘ系统的实现。     

基于JFC/SWING开发数据敏感组件

探讨了 ＪＡＶＡ新一代ＧＵＩ ＡＰＩ Ｓｗｉｎｇ的体系结构及特点，提出了一个使Ｓｗｉｎｇ组件具有数据敏感特性的设计框架，并进行了初步的实现。     

大气污染总量控制规划智能决策支持系统中的知识表示和推理

在大气污染总量控制规划智能决策支持系统（ＩＳＡＰＥＣ）中知识表示方法采用产生式表示法,为提高推理的效率,将ＩＳＡＰＥＣ知识库设计为包含领域级和元级的两级知识库。为了便于用户和领域专家理解,又便于推理的实现,对这两级知识库中的知识都设计内、外两种形式,并且外部形式的知识可通过编译转化为内部形式的知识。针对领域级知识库分别设计了综合应用正向推理和逆向推理优点的目标推理机以及元推理机,此外还设计了推理中     

面象对象用户接口管理系统模型的建立

本文采用面向对象技术，在对用户接口管理系统（ＵＩＭＳ）进行分析的基础上，提出了满足典型应用要求的ＵＩＭＳ模型框架，其目的是建立基于快速原型法的ＵＩＭＳ开发与管理模型。     

基于混合特征的上下位关系验证方法

上下位关系的自动验证是知识获取中的一个关键问题。提出一种基于混合特征的迭代上下位关系验证方法,从语义、语境、空间结构角度,给出一组上下位关系特征,根据抽样数据分析,将所有特征转化为用于验证的产生式规则,利用这些规则对基于模式获取的上下位关系进行循环迭代验证。实验结果说明了该方法的有效性。     

一个高效的关联规则增量式更新算法

针对关联规则的维护问题,设计了一个高效的增量式更新算法ＦＩＵＡ,并将ＦＩＵＡ和已有的ＩＵＡ算法进行了比较,并通过实验证实了ＦＩＵＡ算法的高效性。     

Hierarchical representation of problem-solving knowledge in a frame-based process planning system

In most frame-based reasoning systems, the information being manipulated is represetned using frames, but the problem-solving knowledge that manipulates the frames is represented as production rules. One problem with this approach is that rules are not always a natrual way to represent knowledge; another is that systems containing lots of rules may suffer from problems with “exponetial blowup” in the amount of computation required. This paper describes a way to address these problems by organizing the problem-solving knowledge not as rules, but in a particular kind of frame hierarchy. the approach described in this paper has been implemented in a problem-solving system called SIPP (Semi-Intelligent Process Planner), which produces plans of action for the manufacture of metal parts. the paper gives an overview of SIPP, compares its knowledge representation and problem solving methods to approaches used in other knowledge-based systems, and describes goals for further research.     

A structural equation modeling approach to generate explanations for induced rules

The performance of an expert system depends on the quality and validity of the domain-specific knowledge built into the system. In most cases, however, domain knowledge (e.g. stock market behavior knowledge) is unstructured and differs from one domain expert to another. So, in order to acquire domain knowledge, expert system developers often take an induction approach in which a set of general rules is constructed from past examples. Expert systems based upon the induced rules were reported to perform quite well in the hold-out sample test.

However, these systems hardly provide users with an explanation which would clarify the results of a reasoning process. For this reason, users would remain unsure about whether to accept the system conclusion or not. This paper presents an approach in which explanations about the induced rules are constructed. Our approach applies the structural equation model to the quantitative data, the qualitative format of which was originally used in rule induction. This approach was implemented with Korean stock market data to show that a plausible explanation about the induced rule can be constructed.     

Checking the consistency of a hybrid knowledge base system

This paper concerns a method to verify the consistency of a hybrid knowledge base system. We assume the knowledge base of the verified system supports the representation of production rules and frame taxonomies. Moreover, the knowledge base can also be used to represent non-monotonic and uncertain reasoning. For the purpose of the verification, an ATMS like theory is created by simulating the deductive process needed to deduce an inconsistency. Next, the ATMS like theory is processed to compute a specification of the initial fact base that allows for the execution of a deductive tree that leads to the inconsistency.     

基础信息层经验规则的一种表达方法

该文讨论在复杂的大型辅助决策系统中,构造智能决策规则模型的一种方法。这是一种基于决策表的知识表示方法。它在传统决策表的基础上,吸收了产生式规则、框架表示法、模糊理论、关系模型等多种方法的思想和技术,把传统决策表加以扩展,得到了一种结构性好、表达能力强、可操作性较好的智能决策表达工具,用来表示大型辅助决策系统中的复杂领域知识,将其中松散的经验规则形式化成智能决策规则模型,从而增强其结构性和可操作性,有效支持对其它信息的操作。     

Case-based reasoning and adaptation in hydraulic production machine design

Case-based reasoning (CBR) can support hydraulic circuit design. Existing expert systems for hydraulic system design use production rules as its source of knowledge. However, this leads to problems of knowledge acquisition and knowledge base maintenance. This paper describes the application of CBR to hydraulic circuit design for production machines, which helps solving problems using past experience. A technique Case-based adaptation (CBA) is implemented in the adaptation stage of CBR so that adaptation becomes much easier. A prototype system has been developed to verify the usefulness of CBR and CBA in hydraulic production machines.     

基于关系数据库的脑血管疾病辅助诊断专家系统

基于关系数据库和VisualBasic6.0设计实现了脑血管疾病辅助诊断专家系统.该系统利用产生式规则表达知识,引入可信度进行不精确推理,在缺乏各项生化检查以及影像学检查的情况下,通过症状、体征等就能为患者给出迅速基本的诊断.     

Prosum-Prolog system for uncertainty management

In this paper we present a system which uses knowledge represented in the form of production rules accompanied by uncertainty degrees. The uncertainty of a rule is given by using the method from SLOP and FRIL: a support pair, which comprises a necessary and possible support and can be interpreted as an interval in which the unknown probability lies. Giving the knowledge in this form, our system generates a Turbo Prolog program which has included the operations for uncertainty management. In this version, two kinds of rules for support logic programming are implemented but the user can propose the other ones, by using the dialogue with the system. Semantic unification differs from that used in FRIL; we use generalized belief functions. © 1997 John Wiley & Sons, Inc.     

An expert system for design for robotic assembly

In recent years, due to the various advantages associated with automation and robotics, much work has been done in developing robotic systems for assembly operations. Since part design plays a major role in assembly, this paper deals with the design of parts for ease of robotic assembly. Considerable knowledge is available in the form of design for robotic assembly rules. In addition, a large amount of data is required for decisions regarding suitability of parts for robotic assembly. The implementation of design for robotic assembly rules would be much easier with the help of an expert system, which would guide the designer toward choosing the design alternative that can best facilitate ease of assembly from a robotic point of view.To this end, a prototype expert system for design for robotic assembly is developed and presented in this paper. The expert system was implemented as a production system, which consists of rules and Object-Attribute-Value (O-A-V) triplets to represent domain knowledge. In order to best utilize the domain specific knowledge, a state space search-based inference mechanism was employed. The implementation of the prototype system is illustrated with examples.     

An IKB defect classification system for automated industrial radiographic inspection

Abstract: This paper presents work undertaken as part of a project concerned with the development of a fully automated industrial radiographic inspection system, based on both conventional image-processing techniques for the detection and analysis of defects in the radiographic image, and intelligent knowledge-based (1KB) techniques for the classification and evaluation of defect data against the quality assurance requirements of the inspection process. In this paper the 1KB defect classification system is presented. This system is based on a hierarchical frame-based knowledge representation and a backward-chaining production rule system. Examples of the frame structures, frame taxonomies and the data-driven procedures, which maintain the knowledge base are given, along with an outline of the defect classification rules and the inference mechanism for dealing with uncertainty by means of confidence factors.     

基于XML的分布式智能故障诊断系统研究

针对分布式智能故障诊断中存在的异构形式知识,文中采用XML技术进行集成,实现知识的统一表示。针对表格等非结构化的原始数据,运用基于人工神经网络的样本学习算法从中提炼得到诊断规则,实现知识的自动化获取。在此基础上,以Java、XML和Web为支撑技术,开发了一个分布式智能故障诊断原型系统DIFD,构建了该系统的三层体系结构,给出了其工作流程。并将该原型系统应用于某炼油厂的机组故障诊断实际中,试运行情况良好。