Hybrid expert systems: A survey of current approaches and applications

This paper is a statistical analysis of hybrid expert system approaches and their applications but more specifically connectionist and neuro-fuzzy system oriented articles are considered. The current survey of hybrid expert systems is based on the classification of articles from 1988 to 2010. Present analysis includes 91 articles from related academic journals, conference proceedings and literature reviews. Our results show an increase in the number of recent publications which is an indication of gaining popularity on the part of hybrid expert systems. This increase in the articles is mainly in neuro-fuzzy and rough neural expert systems’ areas. We also observe that many new industrial applications are developed using hybrid expert systems recently.     

Development of expert control systems: A pattern classification and recognition approach

In this paper, a pattern classification and recognition approach to expert control systems is developed for use in the on-line analysis and design of dynamic systems. The approach used is based on the tuning of a three-term PID controller and, hence, it is not dependent on a specific form of the process model. A real-time experiment of implementing the developed controller using a microcomputer and associated hardware is presented. A sample set of production rules is discussed. The expert system reaches appropriate tuning parameters, using extracted features, such as oscillatory, underdamped, and exponentially monotonic properties.     

A Delphi-based approach to developing expert systems with the cooperation of multiple experts

Knowledge acquisition has been a critical bottleneck in building knowledge-based systems. In past decades, several methods and systems have been proposed to cope with this problem. Most of these methods and systems were proposed to deal with the acquisition of domain knowledge from single expert. However, as multiple experts may have different experiences and knowledge on the same application domain, it is necessary to elicit and integrate knowledge from multiple experts in building an effective expert system. Moreover, the recent literature has depicted that “time” is an important parameter that might significantly affect the accuracy of inference results of an expert system; therefore, while discussing the elicitation of domain expertise from multiple experts, it becomes an challenging and important issue to take the “time” factor into consideration. To cope with these problems, in this study, we propose a Delphi-based approach to eliciting knowledge from multiple experts. An application on the diagnosis of Severe Acute Respiratory Syndrome has depicted the superiority of the novel approach.     

Institutionalizing expert systems: Guidelines and legal concerns

Often, knowledge engineers become so involved in the development process of the expert system that they fail to look further down the road toward the expert system's institutionalization within the organization. Institutionalization is an important component of the expert system planning process. More specifically, the legal issues associated with expert systems development and deployment are critical institutionalization factors. This paper looks at some expert system institutionalization guidelines, and then focuses on legal considerations. Adapted from Zeide, J. S. and J. Liebowitz, “Institutionalizing Expert Systems: Guidelines and Legal Concerns,” Proceedings of FLAIRS-92 Conference, Ft. Lauderdale, FL.     

Human factors in information technology: The socio-organisational aspects of expert systems design

This paper looks beyond the mostly technical and business issues that currently inform the design of knowledge-based systems (e.g., expert systems) to point out that there is also a social and organisational (a socio-organisational) dimension to the issues affecting the design decisions of expert systems and other information technologies. It argues that whilst technical and business issues are considered before the design of Expert Systems, that socio-organisational issues determine the acceptance and long-run utility of the technology after it has been implemented. It shows how four issues within the organisation can affect the design or the after-effects of the design and implementation of the technology. It also shows how the four issues can be considered within the structured phases of expert system development.     

Two approaches to developing expert systems: A consideration of formal and semi-formal domains

The conventional approach to developing expert systems views the domain of application as being formally defined. This view often leads to practical problems when expert systems are built using this approach. This paper examines the implications and problems of the formal approach to expert system design and proposes an alternative approach based on the concept of semi-formal domains. This approach, which draws on the work of socio-technical information systems, provides guidelines which can be used for the design of successful expert systems.     

On the selection of equity securities: An expert systems methodology and an application on the Athens Stock Exchange

In this article we present an expert systems methodology for supporting decisions that concern the selection of equities, on the basis of financial analysis. The proposed methodology is employed for selecting the attractive equities, through the evaluation of the overall corporate performance of the corresponding firms. The crucial importance issue of the industry/sectoral accounting singularities was strongly taken into account. An elaborate review of coherent research studies is also provided. Finally, the validity of the proposed methodology is tested through a large scale application on the Athens Stock Exchange.     

ROGET: A knowledge-based system for acquiring the conceptual structure of a diagnostic expert system

This paper describes ROGET, a knowledge-based system that assists a domain expert with an important design task encountered during the early phases of expert-system construction. ROGET conducts a dialogue with the expert to acquire the expert system's conceptual structure, a representation of the kinds of domain-specific inferences that the consultant will perform and the facts that will support these inferences. ROGET guides this dialogue on the basis of a set of advice and evidence categories. These abstract categories are domain independent and can be employed to guide initial knowledge acquisition dialogues with experts for new applications. This paper discusses the nature of an expert system's conceptual structure and describes the organization and operation of the ROGET system that supports the acquisition of conceptual structures.     

Decision making,computer attitudes and expert systems: What is our direction?

Expert systems have been concerned with applications dealing with medical diagnosis, mineral exploration, and computer configuration, with some efforts relatively successful in achieving results at least as good as human experts. Today, much is being written about these systems and managerial decision-making activities in organizations and the positive impact that they can have in these situations. However, it appears that expert systems could become somewhat of a panacea for some organizational ailments as research, development, and marketing of them continues at a fast pace. What may be forgotten in this technological thrust is the individual decision maker and his/her unique style of decision making which could affect acceptance and use of these systems. Another important consideration is the attitude people have toward computers and computer systems, which along with decision-making styles could certainly affect expert system effectiveness and ultimate success in organizations. This paper provides a discussion of potential problems that could occur regarding individual decision making and attitudes and their relationships to these systems.     

Rule-based expert systems to support step-by-step guidance in algebraic problem solving: The case of the tutor PAT2Math

In order for an Intelligent Tutoring System (ITS) to correct students’ exercises, it must know how to solve the same type of problems that students do and the related knowledge components. It can, thereby, compare the desirable solution with the student’s answer. This task can be accomplished by an expert system. However, it has some drawbacks, such as an exponential complexity time, which impairs the desirable real-time response. In this paper we describe the expert system (ES) module of an Algebra ITS, called PAT2Math. The ES is responsible for correcting student steps and modeling student knowledge components during equations problem solving. Another important function of this module is to demonstrate to students how to solve a problem. In this paper, we focus mainly on the implementation of this module as a rule-based expert system. We also describe how we reduced the complexity of this module from O(n^d) to O(d), where n is the number of rules in the knowledge base, by implementing some meta-rules that aim at inferring the operations students applied in order to produce a step. We evaluated our approach through a user study with forty-three seventh grade students. The students who interacted with our tool showed statistically higher scores on equation solving tests, after solving algebra exercises with PAT2Math during an approximately two-hour session, than students who solved the same exercises using only paper and pencil.     

Expert systems in ergonomics: requirements and an approach

Abstract

Industry currently fails to derive maximum benefit from ergonomics. This is mainly due to an imbalance between the large amount of ergonomie knowledge available and the limited amount actually applied. The use of the methodology of expert systems in ergonomics is one possibility for reducing this imbalance. This paper presents basic requirements for the development of expert systems. The particular requirements for the application of expert systems in ergonomics are also derived. Finally, the stage of development of an expert system for assessing lifting and carrying tasks is presented, and practical examples for the application of the system are discussed.     

Selection of knowledge acquisition techniques based upon the problem domain characteristics of production and operations management expert systems

The application of expert systems to various problem domains in business has grown steadily since their introduction. Regardless of the chosen method of development, the most commonly cited problems in developing these systems are the unavailability of both the experts and knowledge engineers and difficulties with the process of acquiring knowledge from domain experts. Within the field of artificial intelligence, this has been called the 'knowledge acquisition' problem and has been identified as the greatest bottleneck in the expert system development process. Simply stated, the problem is how to acquire the specific knowledge for a well-defined problem domain efficiently from one or more experts and represent it in the appropriate computer format. Given the 'paradox of expertise', the experts have often proceduralized their knowledge to the point that they have difficulty in explaining exactly what they know and how they know it. However, empirical research in the field of expert systems reveals that certain knowledge acquisition techniques are significantly more efficient than others in helping to extract certain types of knowledge within specific problem domains. In this paper we present a mapping between these empirical studies and a generic taxonomy of expert system problem domains. In so doing, certain knowledge acquisition techniques can be prescribed based on the problem domain characteristics. With the production and operations management (P/OM) field as the pilot area for the current study, we first examine the range of problem domains and suggest a mapping of P/OM tasks to a generic taxonomy of problem domains. We then describe the most prominent knowledge acquisition techniques. Based on the examination of the existing empirical knowledge acquisition research, we present how the empirical work can be used to provide guidance to developers of expert systems in the field of P/OM.     

Expert systems in production planning and scheduling: A state-of-the-art survey

Intelligent solutions, based on expert systems, to solve problems in the field of production planning and scheduling are becoming more and more widespread nowadays. Especially the last decade has witnessed a growing number of manufacturing companies, including glass, oil, aerospace, computers, electronics, metal and chemical industries—to name just a few—interested in the applications of expert systems (ESs) in manufacturing. This paper is a state-of-the-art review of the use of ESs in the field of production planning and scheduling. The paper presents famous expert systems known in the literature and current applications, analyzes the relative benefits and concludes by sharing thoughts and estimations on ESs future prospects in this area.     

Characterization and analysis of sales data for the semiconductor market: An expert system approach

Chip purchasing policies of the Original Equipment Manufacturers (OEMs) of laptop computers are characterized by similarity measures and probabilistic rules. Our main goal is to build an expert system for predicting purchasing behavior in the semiconductor market. The probabilistic rules and similarity measures are extracted from data of products bought by the OEMs in the semiconductor market over twenty quarters. We present the data collected and different qualitative data mining approaches to analyze and extract rules from the data that best characterize the purchasing behavior of the OEMs. Our analysis of the similar product selection shows that there are two main groups of OEMs buying similar products. Using our probabilistic rules, we obtain an average score of approximately 95% reconstructing quarterly data for a one year window.     

Human systems design criteria: State of the art[1979] and future perspectives

This paper deals with the problem of designing more humanised computer systems. This problem can be formally described as the need for defining human design criteria, which — if used in the design process - will secure that the systems designed get the relevant qualities. That is not only the necessary functional qualities but also the needed human qualities.The author's main argument is, that the design process should be a dialectical synthesis of the two points of view: Man as a System Component, and System as Man's Environment. Based on a man's presentation of the state of the art a set of design criteria is suggested and their relevance discussed.The point is to focus on the operator rather than on the computer. The crucial question is not to program the computer to work on its own conditions, but to “program” the operator to function on human conditions.     

A systems ergonomics analysis of the Maidstone and Tunbridge Wells infection outbreaks

This paper describes a systems ergonomics analysis of the recent outbreaks of Clostridium difficile, which occurred over the period 2005–07 within the UK Maidstone and Tunbridge Wells NHS Trust. The analysis used documents related to the outbreak, alongside the construction of a system model in order to probe deeper into the nature of contributory factors within the Trust. The findings from the analysis demonstrate the value of looking further at cross-level and whole-system aspects of infection outbreaks. In particular, there is a need for further study of the causal relationships that exist between hospital management and clinical management levels within the system. Finally, the paper discusses ways forward and strategies that could be adopted in order to limit the outbreak of hospital-related infections and shape future research. The approach used for the system analysis described in the paper could be used by healthcare practitioners and ergonomists to probe deeper into the causes of infection outbreaks and to extend the scope of interventions aimed at preventing their occurrence.     

Expert systems as extensions of the human mind: A user oriented,holistic approach to the design of multiple reasoning system environments and interfaces

Expert systems have had little impact as computing artifacts. In this paper we argue that the reason for this stems from the underlying assumption of most builders of expert systems that an expert system needs to acquire information and to control the interaction between the human user and itself. We show that this assumption has serious linguistic and usability flaws which diminish the likelihood of producing socially acceptable expert systems. We propose a reversal of this paradigm, for the design of expert systems, by assuming that it is the human user who needs to acquire information and to control the interaction between themselves and the system.     

Innovating with enterprise systems and digital platforms: A contingent resource-based theory view

In an era of new technological advances and hyper-competition, it is no surprise that organizational innovation enabled through information systems in order to achieve competitive parity will remain a core topic of interest for both scholars and practitioners. Understanding the process of innovation through enterprise systems (ES) is especially critical, given the contradictory beliefs surrounding the role of ES in organizational innovation. Conversely, recent anecdotal commentary suggests a substantial growth in digital platforms, purportedly energizing innovation. This study seeks to address our limited understanding of how digital and ES platforms attain innovation, through a study involving 189 organizations.     

Understanding the influence of information systems competencies on process innovation: A resource-based view

The resource based view of firms is used to explore how information system (IS) competencies affect process innovation in an organization. Data was collected through a case study of two process innovations at a healthcare firm in the United States. The findings illustrate how six IS competencies – Knowledge Management, Collaboration, Project Management, Ambidexterity, IT/Innovation Governance, Business-IS Linkages – can differentially affect the conception, development and implementation of process innovations. Implications for researchers and practitioners are drawn from these conclusions and suggestions for further research are proposed.