Expert Decision Support System Research Articles

CALEX/Peaches, an Expert System for the Diagnosis of Peach and Nectarine Disorders

Abstract An expert decision support system for agricultural management called CALEX is currently being developed. The program runs on any IBM compatible personal computer with 256K or more of memory and either two floppy disk drives or a hard disk and one floppy disk drive.

Increasing Integration in Information Technology and Communication Systems

Recent developments in information technology and communication systems permit greater overall integration of technical, human and organizational systems. Evolutionary transitions from electronic data processing (EDP) and management information systems (MIS) are extended in new knowledge systems, decision support systems (DSS), expert systems (ES) and artificial intelligence (AI) systems. Increased integration permits developing more complete management support systems (MSS) with multiple options and interactive strategic management plans and controls. ‘The significance of interactive and integrative, systemic management is that it helps managers see a panorama instead of a limited picture. It builds added awareness and incorporates feedback into the overall dynamic practice of management’. August W. Smith, Stages of Management Evolution Intersystems Publishers, 1987, pp. 74–75.

Automated interpretation of brainstem auditory evoked potentials: a prototype system

This paper describes a preliminary version of an expert decision support system for interpretation of brainstem auditory evoked potentials. The design combines an analytical signal processing module with a rule-based module that incorporates the kinds of heuristic criteria used by human interpreters. The prototype system determines whether a sensory response is present in the waveform; if so, it identifies peak V, the most prominent peak. A level of confidence is associated with the identification. Results of applying the system to a test set of 20 waveforms, including some waveforms from comatose patients that showed no sensory response, are described. The system performed well when a response was present, but it was not as effective in interpreting waveforms with no response present.

The Decentralization of Management Science and the Birth of Self-Starters

In this paper, the authors provide a commentary on current trends in management science. This commentary is based largely on US experience gleaned from published material. This material indicates that the environment of management science is rapidly changing. Personal computers, end-user computing, the information centre, other information system elements and the general competitive state of many US organizations provide significant changes. Opportunities for interdisciplinary activity, through decision support systems, expert systems, strategic planning and material requirements planning, exist even more than in the past. This opportunity for growth may occur through ‘self-starters’. Self-starters are line managers who develop their own management science projects without direction from above or the direct assistance of management science staff. The current environment, the decentralization of management science and the birth of self-starters are discussed, as well as implications of this trend.

Decision support system research at Leicester Polytechnic

Leicester Polytechnic Library has recently completed a research programme for the British Library Research and Development Department into the application of office automation and decision support systems in particular to the library environment. Decision support systems (DSS) can seen as an extension of the idea of management information systems by providing a broader range of information in a more flexible and interactive way. There is a wide range of computer software claiming to offer decision support ranging from spread‐sheets at one end of the spectrum to knowledge based, or expert DSS programs, with proportional variations in cost. For this reason a definition of a DSS is difficult to establish but the major components of a system are generally considered to be:

Problem-knowledge coupling: a tool for physical therapy clinical practice.

The purposes of this article are 1) to summarize the development, function, and philosophy of the Problem-Knowledge Coupler (PKC), a computerized tool that is designed to aid the clinical decision-making process in medical practice, and 2) to speculate on the value this system has in meeting clinical practice, needs and addressing professional practice issues in physical therapy. The evolution of the PKC system from its origins in the problem-oriented system of medical care is described, and the philosophy of problem-knowledge coupling is contrasted to the basic philosophy of traditional clinical medical practice and never computerized expert decision-support systems. We suggest that problem-knowledge coupling could be a useful tool in physical therapy because it improves the collection and synthesis of patient information and uses the unique nature of individual patient problems coupled with the clinical literature as the bases for clinical practice decisions.

An expert decision support system for assisting power system operators to correct real power flow violations

Abstract This paper presents an expert decision support system which incorporates operator knowledge for correcting real power flow violations in a power system. Details of the implementation are given and the potential of the system is assessed. Rule-based programming techniques are used, the tool being the production system language OPS5+.

Integrating an Expert System and DSS for Strategic Decision Support

This article describes the methodology, design, and evaluation of an integrated strategic decision support and expert system called SUCCESS for use by senior management. It was developed to assist top managers of strategic business units SBU's in business strategy formulation. SUCCESS allows managers to evaluate their own and their competitor's strategy in terms of nine well-known typologies. Furthermore, it can be used to assist managers in determining the implications of proposed strategy changes. SUCCESS uses an expert knowledge base which defines each of the potential strategies in terms of28 variables to determine which strategy is matched most closely.

The evolution of an expert DSS for electric utility load research

Load research conducted by electric utility companies is an activity embracing the measurement and study of electrical load to understand the trends and behavior of electric utility consumption. The results of load research are major determinants in rate design and capacity planning for the electric utility company. Accurate load research is imperative for a well managed electric utility. The information base used in load research consists of customer billing data and sample data collected under strict guidelines set by the Public Utilities Regulatory Policies Act. Selection of appropriate sampling procedures is a central function of load research. This paper describes the evolution of an integrated expert decision support system (XDSS) for load research sample design. It is an exploratory system that has a potentially large impact on the profitability of electric utility companies. It was the result of a consulting project begun 4 years ago with a medium sized utility company. Much of the underlying statistical sampling methodology in the XDSS had to be newly derived to meet the specific needs of sampling in load research.

An integrated expert decision support system for agricultural management

This paper describes the CALEX system, a microcomputer based integrated expert decision support system for agricultural management. The program, which is implemented in conjunction with domain specific modules, consists of three separate subprograms: an executive, a scheduler, and an expert system shell. The executive serves as the primary interface to the user, to models, and to the disk. The scheduler generates a sequence of management activities by repeatedly activating the expert system. The expert system makes the actual management decisions. The CALEX package is domain independent and can be used with any commodity. Initial development of the program has focused on the development of a package of modules for California cotton and another package for peaches. This paper describes the architecture of the basic CALEX program. The features of the CALEX package are illustrated with brief descriptions of some of the commodity specific implementations. Full descriptions of commodity specific implementations will be given elsewhere.

An artificial intelligence based method for scheduling crop management actions

Development of the prototype version of the CALEX program, an integrated expert decision support system for crop management, indicated that a major weakness of the expert system format was in formulating a schedule of guidelines for management actions. Problems encountered included organizing and integrating knowledge bases for several different types of action (e.g. pest management, irrigation, fertilization, etc.), dealing with the influence that these actions have on each other, and the automated synthesis of the actual guidelines. To solve these problems a scheduling system was developed for the CALEX program based on the concept of the multi-agent planner as developed in artificial intelligence research. This planner was implemented in an object-oriented programming style in the CALEX program. The present paper describes this scheduling and guideline development system.

Value-driven expert systems for decision support

Values are an inherent part of all decision processes. Hence, values are at least implicity included in all expert systems intended for decision support. This paper outlines the concepts and methodology, which are based on the principles and procedures of decision analysis, to address explicity the values in an expert system logically and consistently. Implementation of the concepts and methodology involves the elicitation of values using the same general approach as that used by knowledge engineers to explicate expert knowledge.

Structure and logic in knowledge-based representations of systems simulation models

The paper focuses on the similarity between modelling and knowledge representation, trying to bring together the OR/Systems Science and the Artificial Intelligence views when referring to a computer system simulation, especially of the discrete-event or the network types. The models we consider are generalized activity networks with resources, including either models with a finite lifetime, such as project scheduling networks, or steady state models, such as queueing networks. By enhancing the structure of entities and states and the logic of transitions within a model specification, modularity is improved and one may adopt a more declarative approach. The relational and rule-based representation formalisms are a convenient choice for that purpose. Then, the use of knowledge bases both for the static (i.e. consultative) and the dynamic (i.e. experimental) study of the model turns up to be more natural. Moreover, the task of building an expert system for decision support on system analysis or synthesis becomes easier. The paper reports some original work in the above directions, using a logic programming approach and an associated specification methodology based on general systems concepts.

Detailed Findings of a Survey of OR Society Membership—I: Structure, Education, Functions and Computers

This paper is the first of two to present the detailed findings of a survey carried out on the membership of the OR Society. Preliminary findings were given in an earlier paper. The survey consisted of sending a questionnaire to all members of the OR Society (42% response rate). Reported in detail in this paper are the structure of the respondents, their educational background, functional involvement, skill requirements and use of time division. Also reported is their involvement with computers, decision support systems and expert systems.

Expert Decision-support Systems for Decision-making

Computers have made tremendous contributions towards transactional processing. However, the highest pay-off the computer can make is not in transactional processing but in decision-making. Recently, expert systems have just begun to be used in the decision-making process. Individual technologies alone are inadequate for an effective decision support. The purpose of this paper is to investigate the related issues in decision support and to develop an expert decision support system (EDSS) for combining decision support systems and expert systems into a unified whole for decision support. The emphasis will be on developing a DSS/ES model which can be used to integrate the traditional DSS database and ES knowledge-base for building a user-friendly EDSS.

Expert Decision-support Systems for Decision-making

Computers have made tremendous contributions towards transactional processing. However, the highest pay-off the computer can make is not in transactional processing but in decision-making. Recently, expert systems have just begun to be used in the decision-making process. Individual technologies alone are inadequate for an effective decision support. The purpose of this paper is to investigate the related issues in decision support and to develop an expert decision support system (EDSS) for combining decision support systems and expert systems into a unified whole for decision support. The emphasis will be on developing a DSS/ES model which can be used to integrate the traditional DSS database and ES knowledge-base for building a user-friendly EDSS.

An expert decision support system for production control

The most crucial resource in manufacturing and production is human expertise. Unfortunately it is often the most costly to acquire. Corporate consulting fees and management training expenses testify to this end. Recent advances in artificial intelligence, decision support, and information processing offer a potential solution to this scarcity. The development of expert decision support systems in the production domain may prove to be the productivity theme of the decade. We present OASES (Operations AnalySis Expert System), designed using the XDSS framework proposed in [10] to emulate a consultant and aid management in troubleshooting manufacturing processes.

An entity-relationship approach to decision support and expert systems

There has been an increasing interest in integrating decision support systems and expert systems to provide decision makers a more accessible, productive and domain-independent information and computing environment. In this paper, we review a workstation-based expert decision support system (WXDSS) proposed by Chen and Pruett. A database-oriented design process is discussed consisting of four phases: (1) requirements analysis, (2) conceptual framework, (3) logical design, and (4) physical system implementation. An entity-relationship (ER) approach to the design of conceptual framework is studied. A positive characteristic of the ER approach is that it provides the user an enterprise view of the WXDSS that is independent of how the information is stored and processed.

Framework for Decision‐Making on Implementing Robotics in Construction

The concept of an expert system for decision support in the application of robotics to the performance of construction tasks is presented. The available decision‐support tools are summarized in light of their usefulness in regard to the design of the system's reasoning mechanism. A knowledge‐organization framework is presented, including the discussion of technical and economic decision criteria of site implementation of robots, as well as the presentation of types of data to be supplied for case‐by‐case decision‐making. Sources of construction robot technical knowledge are outlined.

Preliminary Findings of a Survey of OR Society Membership

This paper presents the preliminary findings of a survey carried out into modelling. The survey consisted of sending a questionnaire to all members of the Operational Research Society (42% response rate). The survey investigated the structure of the OR Society membership; the educational background of OR Society members; the functional involvement, skill requirements and time division of OR Society members; the frequency of use of modelling areas by OR Society members; the types of computers used by OR Society members, and their involvement with decision support systems and expert systems. Full details of the survey, questionnaires and results are given in the paper.