A generalized expert system for database design

Generalized Expert System for Database Design (GESDD) is a compound expert system made up of two parts: (1) an expert system for generating methodologies for database design, called ESGM; and (2) an expert system for database design, called ESDD. ESGM provides a tool for the database design expert to specify different design methodologies or to modify existing ones. The database designer uses ESDD in conjunction with one of these methodologies to design a database starting from the requirement specification phase and producing a logical schema in one of the well-known data models, namely, the hierarchical data model, the network data model, or the relational data model. The system is evolutive in the sense that an existing methodology can be modified or a novel methodology can be added to the existing ones. GESDD is a menu-driven system and it is coded in Prolog     

学分制网上选课系统的数据库设计方案

主要探讨了在真正的学分制管理模式下,开发网上选课系统需要解决的主要问题,重点介绍了后台数据库的整体设计思路。     

A fuzzy expert database system

Fuzzy concepts always exist in much of human reasoning as well as decision making. This paper presents a fuzzy expert database system which is an integration of a fuzzy expert system building tool called SYSTEM Z-II and a database management system called Rdb/VMS. This system is able to extract fuzzy data and terms stored in a database and used in the fuzzy reasoning in an expert system. It can also retrieve information by fuzzy database-queries which are generated by the expert system automatically. Many expert systems in different domain areas such as decision making can be constructed. Sample applications are described to demonstrate the flexibility and power of this system. The fuzzy query language defined and used in the system can also be used independently as a fuzzy enquiry tool in database applications.     

Degasification system selection for US longwall mines using an expert classification system

Methane emissions from the active face areas and from the fractured formations overlying the mined coalbed can affect safety and productivity in longwall mines. Since ventilation alone may not be sufficient to control the methane levels on a longwall operation, gob vent boreholes (GVB), horizontal and vertical drainage boreholes, and their combinations are drilled and used as supplementary methane control measures in many mines. However, in most cases, the types of degasification wellbores chosen are decided based on previous experiences without analyzing the different factors that may affect this decision.This study describes the development of an expert classification system used as a decision tool. It was built using a multilayer perceptron (MLP) type artificial neural network (ANN) structure. The ANN was trained using different geographical locations, longwall operation parameters, and coalbed characteristics as input and was tested to classify the output into four different selections, which are actual degasification designs that US longwall mines utilize. The ANN network selected no degasification, GVB, horizontal and GVB, and horizontal, vertical and GVB options with high accuracy. The results suggest that the model can be used as a decision tool for degasification system selection using site- and mine-specific conditions. Such a model can also be used as a screening tool to decide which degasification design should be investigated in detail with more complex numerical techniques.     

An expert system for respirator selection

A Respirator Selection Expert System (RSES) is described which assists the user in selection of a respirator for a specific application. In addition to determining the minimum class of respirator which should be used by following the NIOSH Respirator Decision Logic, RSES also provides all necessary calculations, data for common industrial contaminants and on-line reference material.     

The development of an online knowledge-based videotheodolite measurement system

Videotheodolite measurement systems have been used in various surveying applications for several years. Unfortunately, most of such systems required artificial targets defining object points. To overcome this restriction the texture on the surface of the object can be used to find interesting points. However, well-trained “measurement experts” are required to operate such a measurement system. In order to make such systems easy to use even for non-experts, we extend it by a knowledge-based component which supports the operator. We report on the architecture and functionality of the respective knowledge-based system, its development stage and the promising results obtained in experimentation.     

一种新型在线数据库审计系统

目前,我国计算机信息系统中普遍使用的是国外厂商的数据库管理系统,其内部操作不透明,无法阻止机密信息泄漏、滥用资源等行为,对于安全相要求较高的部门这一后果更为严重.虽然绝大部分数据库管理系统自身带有审计功能,但是它们都存在审计文件格式复杂,开启审计功能后系统性能下降等弊端.提出了一种新型的在线数据库审计系统的设计与实现方法,该方法采用旁路监听方式实时采集客户端对数据库的操作命令,不必修改现有网络结构,不影响正常业务的运行,而且审计信息格式固定,便于审计数据的事后查询和统计分析.     

QFD-based expert system for non-traditional machining processes selection

Selection of an optimal non-traditional machining (NTM) process for generating a desired feature on a given material requires the consideration of several factors among which the type of the workpiece material and shape to be machined are the most significant ones. This paper presents a quality function deployment (QFD) based methodology to ease out the optimal NTM process selection procedure. It includes the design of a QFD-based expert system that can automate the decision making process with the help of graphical user interfaces and visual aids. The developed expert system employs the use of a house of quality (HOQ) matrix for comparison of the relevant product and process characteristics. The weights obtained for various process characteristics are utilized to estimate an overall score for each of the NTM processes. Finally, if some of the NTM processes satisfy certain critical criteria, they are again compared with each other on the basis of their overall scores and the process having the maximum score is selected as the optimal choice.     

An online expert system for fault diagnosis in hydraulic systems

Fault diagnosis has become increasingly important for industrial automation and many approaches have been investigated for the online diagnostic task. This work demonstrates a new online expert system for dynamic industrial automated processes. The emphasis of this diagnostic system lies in the functions provided for fault detection, prediction, compensation and diagnosis. The system uses experiential knowledge cooperatively with scientific knowledge in a new interactive formation. It is developed in two parts using the DASYLab software for the numerical computations and the KPWin development tool for the symbolic representations. The system was developed in collaboration with the company Automation Systems S.A., which specializes in hydraulic systems, and is used for fault detection in production machines.     

基于模糊数据库的专家系统实现方法

介绍了一个仅用Visual Foxpro6．0一种语言实现的专家系统,它以模糊数据库为基础进行机器学习和模糊推理,实现了对装备的故障诊断过程。重点介绍了该系统以理论初值为起点、基于事例的机器学习过程。该系统经维修实践检验,具有较高的稳定性和准确性,显著提高了工作的效率。     

The client-centred approach: expert system development

Abstract: This paper describes a project that is studying an expert system (ES) development method tailored to meet the requirements of small and medium-sized enterprises (SMEs). It is posited that many such organisations cannot use ES technology because of its high entry price and because the available tools and methods were developed for and by large organisations. Within this context our development method encompasses the entire life cycle of an ES from initial conception to implementation through to maintenance and updating. The central premise is that the method should be 'client-centred', emphasising what the client can see, rather than being 'technology-centred', emphasising how the knowledge engineers work. Discussion includes how this methodology addresses many criticisms of current ES development methods, including rapid prototyping and KADS.     

The design of an expert system for inventory control

An expert system for inventory management is presented in this paper. The focus is on the development of a simple, user-friendly tool that can be used effectively by managers to increase the cost-effectiveness of their inventory systems. The expert system is capable of analyzing input parameters by performing statistical analyses of data bases, generating plots and graphs, implementing a set of rules for the selection of inventory models, and choosing a solution procedure. The scope of this paper is limited to the single-item, single-location problems.     

MATISSE: a relational expert system for industrial site selection

This paper reports on the development of a relational knowledge-based decision support system for urban planning in general and industrial site selection in particular. The system treats the concept of site suitability as a matching process, using decision tables (DTs). The proposed computer-based system is tested using the locational choice problem of an industrial company. The system has been given the acronym MATISSE: “Matching Algorithm, A Technique for Industrial Site Selection and Evaluation”. The knowledge base of the system was created by conducting a series of in-depth interviews supplemented with a detailed survey of the relevant literature. Using this information, a series of decision tables could be constructed using prologa95. In total, 90 crisp (sub)decision tables were constructed. This set of DTs can be used as a decision support system to select and evaluate potential sites, given a set of locational requirements.     

Specifying an expert system

The success of numerous expert systems in practical applications warrants a more formal approach to their development and evaluation. Reliability assurance of expert systems requires a methodology for the specification and evaluation of these systems. Expert systems are a new class of software system, but some traditional techniques of software development may be adapted to their construction. However, the specification of an expert system differs from that of a more traditional software program in that parts of the specification are permitted to be only partially described when development starts.

Specifications have two important purposes: as contracts between suppliers and clients, and as blueprints for implementation. A specification consists of a problem specification and a solution specification. The problem specification plays the role of contract and states explicitly what the problem to be solved is, and the constraints that the final product must satisfy. The solution specification plays the role of blueprint and has two major aspects: analyzing how a human expert solves the problem, and proposing an equivalent automated solution. We propose an approach to the specification of expert systems that is flexible, yet rigorous enough to cover the important features of a wide range of potential expert system applications. We describe fully each of the components of an expert system specification and we relate specification to the issues of evaluation and maintenance of expert systems.     

Toward an expert system for chromosome analysis

Automation of chromosome analysis has long been considered as a very difficult task. Efforts to computerize some or all of the procedures using various conventional pattern recognition techniques have had only limited success. In this paper the previous work in this domain is briefly reviewed, with a discussion of the limitations of the existing approaches. An attempt to apply AI techniques is introduced, and the organization of an expert image analysis system for chromosome classification is described, mainly at a conceptual level. Based on the proposed architecture, the low-level processes (segmentation, feature extraction) and the high-level processes (classifications or interpretations) can be carried out in a knowledge-guided fashion with a combinational use of image processing and pattern recognition knowledge, as well as expert chromosome classification knowledge embedded in a rule-based structure. A knowledge-based chromosome image analysis scheme is presented which adopts a hierarchical hypothesize-and-verify paradigm. Example rules are given to illustrate how they can be used in this scheme.     

Natural language interface for an expert system

This paper provides complete analysis of natural language interface from the screen manager to the parser/understander, even though it has some limitations. The main focus is on the design and development of a subsystem for understanding natural language input in an expert system. Fast response time and user-friendliness were the most important considerations in the design. The screen manager provides an easy editing capability for the user. The spelling correction system can detect most spelling errors and correct them automatically, quickly and effectively. The Lexical Functional Grammar (LFG) parser and the understander are designed to handle most types of simple sentences, fragments, and ellipses. As a result, this system as applied to a man-machine dialogue gives improved ill-formed natural language input handling capabilities to the expert system.     

变电站工作票及操作票专家系统的研制

介绍了一套已成功投入使用的变电站工作票及操作票专家系统.该系统的核心模块采用知识工程技术.开列标准票的知识与经验构成规则库,将变电站的网络拓扑结构建立关系型数据库,推理机动态地操纵规则库和数据库.运用面向对象的继承性来构造软件的类体系,把用于安全措施的成员函数和用于操作的成员函数放入同一个类.实现了工作票和操作票的有机结合.利用Delphi6.0建立Access数据库与Excel报表之间的数据通信,实现了自动开票和查询开票的相互转换.     

DCA for online prediction with expert advice

Neural Computing and Applications - We investigate DC (Difference of Convex functions) programming and DCA (DC Algorithm) for a class of online learning techniques, namely prediction with expert...