一种评估专家系统的研究

针对飞行器飞行状态的人工评估日趋复杂和困难的问题,将评估树技术和专家系统技术相结合,提出一种用于飞行器任务评估的综合分析模型。首先介绍系统总体结构设计,分析系统各模块的功能和联系;然后,提出一种知识表示模型以及知识获取与转换流程,建立基于数据库的知识库;最后,分析专家系统推理机制,通过不确定性推理提高系统的推理有效性。工程实践表明该专家系统是可靠有效的。     

基于数据库技术的气流干燥专家系统知识库的建立

针对专家系统中传统知识表示存在的数据修改比较困难．数据与程序之间缺乏独立性，满足不了多用户、多应用共享知识需求的缺陷，故在闪速熔炼气流干燥专家系统中采用数据库技术来实现知识库，提出了基于数据库的知识表示方式，设计了规则库的数据库结构和类结构，然后利用ADO技术实现了对数据库的添加、更新等功能，并应用于知识库，从而可不断地扩充知识库，体现了知识库的健壮性，有益于知识库维护的一致性和完整性。     

基于数据库的一种推理算法

针对当前国内专家系统设计所面临的新问题,综合种种上专家系统的实现方案提出一种基于大数据库管理系统和Ｗｅｂ／Ｓｅｒｖｅｒ结构的大型系统设计方案。为了实现需要提出了产生式系统的关系模型,同时提出了一种可提高数值计算能力和可进行灵活不精确推理能力的知识表示方法。为了提高大型系统的效率,便于实现实用的系统,作者改造了一种基于知识线性排序的搜索算法。     

专家系统中多种知识表示方法的集成应用

专家系统的建立是以知识为基础的，采用何种知识表示方法在一定程度上决定了专家系统能否正确高效的运行。先综合比较了常见的几种知识表示方法，然后介绍了在“现役混凝土结构耐久性评估专家系统”1中集成应用框架、产生式、神经网络等多种知识表示方法的思路及解决方案，该系统的实际使用证明此法是可行和有效的。     

面向对象的故障诊断专家系统深层知识模型

在诊断型化工专家系统中应用深层知识的研究报导已有许多。这些专家系统一般是基于产生式规则的、其缺点是通用性较差,因为深层知识模型会淹没在规则库中,因此、不仅要重视深层知识模型的建立,还应当重视专家系统知识表示在实现该模型中的重要性。本文首先提出了一个新的深层知识模型。该模型把一个复杂的过程分解为一组功能独立的子系统。每个子系统的知识定义为功能描述和行为描述。功能和行为描述用一组约束方程表示。这些约束方程的失衡则表示故障症状。故障被分为两类,即本质故障和原始故障。文中提出了一个模糊集合包含模型用于双症状找出最可能的本质故障。而双本质故障找出原始故障,则采用因果搜索方法。本文接下来讨论了该深层知识模型与面向对象知识表示是相吻合的。从1个复杂系统中抽象出来的子系统在面向对象知识库中被表达为一个知识对象。当这个子系统出现在一个新的化工过程中时,其相应的知识对象也可以用于这个新过程的专家系统知识库中。此外,由于面向对象的方法可以定义为与过程程序语言的接口,因而可以实现定性的基于模型的推理与定量的基于模型的推理的偶合。本文提出的方法已用于一个炼油蒸馏装置离线故障诊断原型专家系统中。     

儿童计划免疫接种专家系统的研究

本文在深入分析和研究儿童计划免疫接种内容的基础上,开发出了一种实用的专家系统,该系统主要由知识库、推理机、知识获取、疫苗接种数据库、儿童基本情况数据库和程序接口等模块了后阐述了该系统中采用的知识表示形式和规则的冲突求解策略。     

模糊Petri网及知识表示

在建造专家系统中虽然有很多种知识表示方法，但都有不尽人意的地方，本文试图用一种新的方法－Ｐｅｔｒｉ网模型来表示知识。本文给出了Ｆｕｚｚｚｙ Ｐｅｔｒｉ网和广义Ｆｕｚｚｙ Ｐｅｔｒｉ网两种模型，并给出了相应的推理算法，一旦专家知识用Ｐｅｔｒｉ网表示后，根据Ｐｅｔｒｉ网固有的特性，我们就能处理专家系统中并行推理、无回溯推理，反向推理等问题。     

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。     

航天器故障诊断专家系统面向对象知识表示的研究

根据航天器系统结构庞大,各子系统相互耦合,稳定性、可靠性要求高等特点。在认真研究典型故障诊断专家系统知识表示的基础上,通过对目前几种常用的知识表示方法的优缺点的分析,提出了航天器故障诊断知识的一种新的表示方法——面向对象知识表示方法。主要介绍了面向对象知识的表示和其推理机制。该方案具有知识层次清晰、知识继承和易于维护等特点,满足航天器复杂大系统的故障诊断需要。     

基于产生式系统的知识建模

如何建立系统完整的专家知识模型,并将其快速映射为面向计算机推理的人工智能语言是当前专家系统研究的重点和难点,而知识表示是其中的关键.本文将模型驱动的思想引入到专家系统领域,定义了一种基于不确定性产生式知识表示的元模型,设计并实现了相应的图形化建模工具和转换引擎,并基于此提出一种新的产生式系统应用框架.该框架在某健康信息评估专家系统中获得了成功的应用.     

Data integration constraints for consistent data redundancy in fuzzy databases

Although the problem of data integration in relational databases has been extensively studied, little work has addressed this problem in the context of fuzzy relational databases. Data integration is highly complex in fuzzy relational databases, partially because of the involvement of the resemblance relation. Inconsistent data redundancy may occur when the fuzzy databases to be integrated are associated with different resemblance relation on a given domain. This work presents the notions of consistency constraints, and applies them to the problem of data integration in several fuzzy data models. The constraints ensure that fuzzy databases with different resemblance relations agree to each other regarding data redundancy. In addition a solution for integrating inconsistent fuzzy databases with minimal information loss is provided. © 2008 Wiley Periodicals, Inc.     

基于ADO的组态软件与关系数据库通信研究

介绍一种基于ADO的工控组态软件与关系数据库通信的方法,并通过一个实例介绍采用ADO组件实现力控组态软件与Ms Access数据库之间数据通信的思路和脚本设计。许多时候,采用工控组态软件开发项目需要解决与关系数据库频繁通信的问题,项目开发者常用的采用SQL函数查询关系数据库的解决方法其操作和具体编程较为复杂。该方法以一种简便、灵活的方式解决上述问题,具有功能强,使用方便,适用范围广等特点。     

Association algebra: a mathematical foundation for object-orienteddatabases

The application of the object-oriented (O-O) paradigm in the database management field has gained much attention in recent years. Several experimental and commercial O-O database management systems have become available. However, the existing O-O DBMSs still lack a solid mathematical foundation for the manipulation of O-O databases, the optimization of queries, and the design and selection of storage structures for supporting O-O database manipulations. This paper presents an association algebra (A-algebra) to serve as a mathematical foundation for processing O-O databases, which is analogous to the relational algebra used for processing relational databases. In this algebra, objects and their associations in an O-O database are uniformly represented by association patterns which are manipulated by a number of operators to produce other association patterns. Different from the relational algebra, in which set operations operate on relations with union-compatible structures, the A-algebra operators can operate on association patterns of homogeneous and heterogeneous structures. Different from the traditional record-based relational processing, the A-algebra allows very complex patterns of object associations to be directly manipulated. The pattern-based query formulation and the A-algebra operators are described. Some mathematical properties of the algebraic operators are presented together with their application in query decomposition and optimization. The completeness of the A-algebra is also defined and proven. The A-algebra has been used as the basis for the design and implementation of an object-oriented query language, OQL, which is the query language used in a prototype Knowledge Base Management System OSAM*.KBMS     

Development of n-tuple algebra for logical analysis of databases with the use of two-place predicates

In designing various programming systems, particularly, simulation systems, the necessity to integrate databases with other programming modules of the system arises. The goal of integration is to lodge the component of interaction with the database with additional capabilities of logical analysis of the subject domain information. In this paper, we propose to extend the mathematical tool of n-tuple algebra to the problem of simulation and analysis of both the relations of relational databases, queries to them, and the logical structures involved in the formation of the subject domain knowledge base.     

关系数据库中的知识发现研究

本文提出了一种关系数据库中的知识发规模型;介绍了相关的机器学习、关系数据库、模糊学和统计学等技术;分析了现有的一些系统;最后,讨论了进一步研究的问题。     

A Multistrategy Approach to Relational Knowledge Discovery in Databases

When learning from very large databases, the reduction of complexity is extremely important. Two extremes of making knowledge discovery in databases (KDD) feasible have been put forward. One extreme is to choose a very simple hypothesis language, thereby being capable of very fast learning on real-world databases. The opposite extreme is to select a small data set, thereby being able to learn very expressive (first-order logic) hypotheses. A multistrategy approach allows one to include most of these advantages and exclude most of the disadvantages. Simpler learning algorithms detect hierarchies which are used to structure the hypothesis space for a more complex learning algorithm. The better structured the hypothesis space is, the better learning can prune away uninteresting or losing hypotheses and the faster it becomes.We have combined inductive logic programming (ILP) directly with a relational database management system. The ILP algorithm is controlled in a model-driven way by the user and in a data-driven way by structures that are induced by three simple learning algorithms.     

通用关系数据库访问层的设计与实现

在目前的软件开发中,面象对象技术和关系数据库技术都扮演着重要的角色。但是,这两项技术之间存在着著名的不匹配问题。论文通过引入一种精心设计的持久化层,对解决该问题提供了一种新颖且有效的方法。     

A semantic framework of the multilevel secure relational model

A multilevel relational database represents information in a multilevel state of the world, which is the knowledge of the truth value of a statement with respect to a level in a security lattice. The authors develop a semantic framework of the multilevel secure relational model with tuple-level labelling, which formalizes the notion of validity in multilevel relational databases. They also identify the multilevel security properties that precisely characterize the validity of multilevel relational databases, which can be maintained efficiently. Finally, they give an update semantics of the multilevel secure relational model that preserves both integrity and secrecy