Building a financial diagnosis system based on fuzzy logic production system

The purpose of this study is to build a financial expert system based on fuzzy theory and Fuzzy LOgic Production System (FLOPS), which is an expert tool for processing the ambiguity. The study consists if four parts. For the first part, the basic features of expert systems are presented. For the second part, fizzy concepts and the evaluation of classical expert systems to fuzzy expert systems will be presented. For the third part, the expert system shell (FLOPS) used in this study will be described. For the last part, it will be presented the financial diagnosis system, developed by using the Wall's seven ratios, traditional seven ratios and also 34 ratios selected by a financial expert. After analyzing and investigating these three kinds of methods, financial diagnosis system will be developed as a fuzzy expen system which used a membership function based on averages and standard deviation. At the last step, the new approach will be tried by increasing the fuzzy sets for five membership functions. Some practical examples will be given. Throughout the paper, the way of building a financial diagnosis system based on fuzzy expert system is stressed.     

Multi-domain expert systems

Abstract: The current trend in expert system building is domain-specific, i.e. there is one expert system for each problem domain. The increased involvement of computers in the decision-making process will inevitably lead to increased demand for expert systems. Based on the current approach to expert systems building, there will be a further proliferation of domain-specific expert systems. This is because each application area produces an expert system tailored to its requirements. This manner of producing expert systems is inadequate and an increased expectation in the performance of expert systems will eventually call for a new approach to constructing them. This paper examines the growth in the use of expert systems, looks into the limitations and problems associated with present-day domain-specific expert systems and suggests a multi-domain expert system architecture as a solution to the problem of increasingly disjointed domain-specific expert systems resulting from uncontrolled proliferation.     

基于虚拟仪器技术的故障诊断专家系统的实现

随着计算机技术的发展,智能技术在测试领域显得越来越重要,在传统的测试系统中使用专家系统技术成为测试系统的发展趋势;文章通过对专家系统原理的介绍,提出了将专家系统技术引入测试领域的可行性,并分别介绍了基于虚拟仪器的测试系统软件设计方法和基于规则的专家系统软件设计方法,并给出了故障诊断专家系统的实现方法和实时故障专家系统的设计方案;经使用后,认为专家系统技术将有助于智能化故障诊断的实现,并且可提高测试技术的智能化程度。     

Using artificial intelligence in communication system design

The authors describe a knowledge-based design support system, called KDSS, that will help designers inexperienced in communication system design easily create advanced systems like intelligent networks, and large-scale distributed computing systems. They began by designing a support system for protocol and communication software. They then experimented with applying expert-system technology in design support systems and developed an expert system for protocol synthesis called KSPS. An expert system for protocol and communication software design that is based on the earlier work is also part of KDSS     

Expert Recommender: Designing for a Network Organization

Recent knowledge management initiatives focus on expertise sharing within formal organizational units and informal communities of practice. Expert recommender systems seem to be a promising tool in support of these initiatives. This paper presents experiences in designing an expert recommender system for a knowledge-intensive organization, namely the National Industry Association (NIA). Field study results provide a set of specific design requirements. Based on these requirements, we have designed an expert recommender system which is integrated into the specific software infrastructure of the organizational setting. The organizational setting is, as we will show, specific for historical, political, and economic reasons. These particularities influence the employees’ organizational and (inter-)personal needs within this setting. The paper connects empirical findings of a long-term case study with design experiences of an expertise recommender system.     

On commercial expert systems projects

The development process of expert systems obeys to rules, which have no counterparts in traditional software engineering techniques. To a certain extent they even contradict them.

AI engineers in charge of the realization of industrial expert systems must be aware of this situation and be prepared to respond to it by providing technology transfer. As long as this transfer to the customers has not happened, commercial expert system projects will lead to frustration and compromises hampering the achievement of the economic objectives set to the projects. For the time being technology transfer must be a major task of AI companies.     

Using hybrid expert system approaches for engineering applications

In this paper, the use of hybrid expert system shells and hybrid (i.e., algorithmic and heuristic) approaches for solving engineering problems is reported. Aspects of various engineering problem domains are reviewed for a numer of examples with specific applications made to recently developed prototype expert systems. Based on this prototyping experience, critical evaluations of and comparisons between commercially available tools, and some research tools, in the United States and Australia, and their underlying problem-solving paradigms are made. Characteristics of the implementation tool and the engineering domain are compared and practical software engineering issues are discussed with respect to hybrid tools and approaches. Finally, guidelines are offered with the hope that expert system development will be less time consuming, more effective, and more cost-effective than it has been in the past.This paper is an attempt to provide some guidelines to expert system development based on limited experience with a handful of tools. It is not the intent of this paper to recommend or endorse the software, manufacturers, or organizations named within, nor to slight others not mentioned. We would appreciate feedback on omissions or oversights, so that more objective information about specific tools can be made public.Work performed while Aerospace Engineer, Artificial Intelligence Section, Mission Planning and Analysis Division, NASA/Johnson Space Center, Houston, TX.     

Some legal aspects of expert systems

As expert systems become more popular, the possibility of lawsuits arising from their use becomes increasingly evident. The expert system developer needs to be aware of important legal concepts associated with an expert system's development and deployment. This paper will primarily explore the rights to intellectual property associated with an expert system and liability for malfunction of an expert system.     

Modelling the software development process using an expert simulation system having fuzzy logic

This paper describes an intelligent computerized tool designed to aid managers of software development projects in planning, managing and controlling the development process of medium- to large-scale software projects. Systems dynamics is used to model and simulate the dynamic process of software development. The software development process is affected by some imprecise and vague variables that are treated as fuzzy variables. The simulation model is integrated with two expert systems. The fuzzy input variables to the system dynamics simulation model are handled by an input expert system having fuzzy logic. This expert system is designed to check the consistency of input variables. The simulation results are analysed by an output expert system having fuzzy logic. This expert system is designed to make recommendations based on experimentation with the simulation model.     

Developing maintainable expert systems using case-based reasoning

Abstract: Maintainability problems associated with traditional software systems are exacerbated in rule-based systems. The very nature of that approach — separation of control knowledge and data-driven execution — hampers maintenance. While there are widely accepted techniques for maintaining conventional software, the same is not true for rule-based systems. In most situations, both a knowledge engineer and a domain expert are necessary to update the rules of a rule-based system. This paper presents, first, an overview of the software engineering techniques and object-oriented methods used in maintaining rule-based systems. It then discusses alternate paradigms for expert system development. The benefits of using case-based reasoning (from the maintenance point of view) are illustrated through the implementation of a case-based scheduler. The main value of the scheduler is that its knowledge base can be modified by the expert without the assistance of a knowledge engineer. Since changes in application requirements can be given directly to the system by the expert, the effort of maintaining the knowledge base is greatly reduced.     

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.     

Expert system evaluation techniques: a selected bibliography

Abstract: The rapid growth in the use of expert systems has led to widespread interest in techniques for their evaluation, which includes verification and validation. Evaluation techniques in the software engineering community are well established but there are different opinions about the effectiveness of transferring software engineering methodologies to expert systems. This paper outlines some of the issues involved in evaluating expert systems and cites almost 200 significant papers on the topic. We present it with the expectation that it will help both new and established researchers become acquainted with the literature of an important and growing field.     

Management applications of expert systems

The development of expert systems for such professionals as doctors diagnosing and treating infectious diseases and geologists exploring for mineral deposits has led to suggestions that expert systems be developed for managers in public and private organizations who make manufacturing, marketing, financial, personnel, and other decisions. This paper describes briefly some of the systems of this type that have already been developed, with an emphasis on the logic expressions used in them, examines other fruitful areas for system development, and identifies software requirements for the implementation of such systems.     

An evaluation of expert system development tools

Abstract: There is a significant amount of interest in expert systems and the software tools that are available for developing these systems. Most tools that are developed at university research labs are described in some detail in books, articles, or technical reports. However, there is a need for objective information on commercial software tools for building expert systems. These tools can be used for research, prototyping and developing end-user applications. Necessarily we must establish a set of criteria which can be used to evaluate these tools. These criteria include an evaluation of the basic features, the development environment, what a tool can be used for, how easy it is to learn and use, how much it costs, and how it is supported. In the first part of this paper, a set of criteria is described for evaluating expert system software tools. In the second part, these criteria are used to evaluate several currently available commercial tools.     

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.     

Expert system-user integrated adaptive systems

Many expert systems operate in dynamic environments where various pertinent environmental variables and conditions vary with the passage of time. These environmental variables and conditions may affect both the set of conditions applied to input variables of expert systems and the set of recommendations provided by expert systems. For this reason, expert systems developed according to dynamic structure will generate timely recommendations. To incorporate dynamic characteristics into the structure of expert systems, it is necessary to develop expert systems as adaptive systems. This paper intends to integrate concepts of learning and adaptiveness into expert system technology.

Expert systems used to assist loan officers in improving the decision-making process of commercial loans are typical examples of expert systems that operate in dynamic environments. This paper illustrates that the quality of information provided to loan officers by expert systems may be improved when expert systems are designed as adaptive expert systems.     

Graphics as an expert system user interfacing media

This paper demonstrates the usefulness of using graphics as an user interfacing media in expert systems. The graphics interfacing ability of the Personal Consultant Plus, an expert system development tool, is examined. A graphics image can be created by a graphics editor or a sophisticated drafting software package, such as TelePaint, PC Palette, Story Board, AutoCAD, etc. The graphics image can then be captured and utilized in the expert system in various ways. The user interface using graphics makes an expert system easier to use and to understand.     

Expert systems integrated with information systems

Amongst the users of the AIDA applications there is a rapidly growing interest in the use of expert systems, not as independent systems, but as logical extensions of their already existing information systems. In this paper a prototype system (IDEA) will be described that consists of a set of utilities for the construction of an expert system within the context of an AIDA application. Although IDEA does not excel in sophisticated knowledge representations nor in search strategies (the development of which was not our primary concern) it is able to demonstrate that the facilities provided by AIDA together with the IDEA facilities result in an expert system which is characterized by a high degree of integration with the already operational information system.     

Informatics for the Law: LEXIS—A legal expert system on Italian family law

This paper describes the LEXIS project, a research endeavor in building a legal expert system on Italian family law. An expert system shell, Xi Plus, was used to help construct this expert system. This paper will describe some of the development steps of this project and also cite some research issues in building legal expert systems.