A reasoning method for a ship design expert system

Abstract: The ship design process is a highly data‐oriented, dynamic, iterative and multi‐stage algorithm. It utilizes multiple abstraction levels and concurrent engineering techniques. Specialized techniques for knowledge acquisition, knowledge representation and reasoning must be developed to solve these problems for a ship design expert system. Consequently, very few attempts have been made to model the ship design process using an expert system approach. The current work investigates a knowledge representation–reasoning technique for such a purpose. A knowledge‐based conceptual design was developed by utilizing a prototype approach and hierarchical decompositioning. An expert system program called ALDES (accommodation layout design expert system) was developed by using the CLIPS expert system shell and an object‐oriented user interface. The reasoning and knowledge representation methods of ALDES are explained in the paper. An application of the method is given for the general arrangement design of a containership.     

Integrating artificial neural networks with rule-based expert systems

The Rule-Based (RB) and the Artificial Neural Network (ANN) approaches to expert systems development have each demonstrated some specific advantages and disadvantages. These two approaches can be integrated to exploit the advantages and minimize the disadvantages of each method used alone. An RB/ANN integrated approach is proposed to facilitate the development of an expert system which provides a “high-performance” knowledge-based network, an explanation facility, and an input/output facility. In this case study an expert system designed to assist managers in forecasting the performance of stock prices is developed to demonstrate the advantages of this integrated approach and how it can enhance support for managerial decision making.     

An investigation of expert systems for die design

This article introduces fuzzy set theory to process the design details of the uncertain portion in die design, and assist the designer to transform those design items with fuzziness into those with definite and reasonable design attributes. For the design parameters of die block thickness, die clearance angle and die sets choice in die design, which possess intermediate features, fuzzy cluster analysis is used to obtain the design attributes. As for single-sided die clearance, stripper pressure and guide bushing-type die design, whose theory or empirical formulas possess uncertainty coefficients or preference design parameters, the fuzzy weighted average method is adopted to obtain the feature parameters that conform with the die design requirement. This study established an expert system prototype to combine the aforementioned uncertainty problems into two kinds of die design, and help the designer obtain a definite design strategy when faced with uncertain design items.     

The design process of expert systems development: some concerns

Abstract: A discussion is presented of why some expert systems that organizations have developed are not successful. The concept of design process plays a very significant role at the outset of the expert system development process. This concept has not been the subject of much debate and attention in expert systems development. From the author's point of view, one of the main issues is how the designer (knowledge engineer) thinks about the design process. In general, the designer's process is influenced by the knowledge engineer's conception. This paper endeavors to disclose some of the main factors related to the knowledge engineer's conception of the design process and an attempt is made to put forward a conceptual model of the expert system design process. This conceptual model is an initial step towards a successful implementation of expert system projects.     

ADO在故障诊断专家系统中的应用

作为新型的数据库访问技术，简要介绍了ADO技术及其特点，重点介绍了ADO技术在专家系统中的应用，利用ADPO技术实现了对两个数据源的访问，为建立在自动测试系统上的故障诊断专家系统提供了入口参数，最后用Visual C 语言实现了编程。     

An explanation shell for expert systems

We describe a shell for expert systems written in Prolog. The shell provides a consultation environment and a range of explanation capabilities. The design of the shell is modular, making it very easy to extend the shell with extra features required by a particular expert system. The novelty of the shell is twofold. Firstly, it has a uniform design consisting of an integrated collection of meta-interpreters. Secondly, there is a new approach for explaining 'why not,' when a query to the system fails.     

Framework for building rule-based machine diagnostic expert systems

In the endeavour to build an expert system called XBAK using Personal Consultant Plus for the diagnosis of sophisticated equipment used in microchip manufacturing, a rule-based machine diagnostic expert system architecture was developed. The approach, features and technical implementation of this application-independent problem-solving structure are described. The architecture can be used as a framework for solving similar problems in the area of machine diagnostics.     

Internet-based expert systems

The Internet offers a large potential for delivery of various information-based services, including the services of intelligent applications. As the availability of the Internet has grown, its value as a medium for the delivery of expert systems in particular has increased. There are now a large number of expert systems available on the Internet, including applications in industry, medicine, science and government. Though the Internet provides several advantages for expert system development, it also presents some special problems. These advantages and disadvantages are explored in more detail in this paper. The paper also presents a review of several Internet-based expert systems with a representative sample of publicly available applications, and a discussion of typical tools for developing Internet-based expert systems. A case study of an Internet-based expert system is presented as well.     

Flexible control in expert systems for construction tasks

In most expert systems for constructional tasks, the knowledge base consists of a set of facts or object definitions and a set of rules. These rules contain knowledge about correct or ideal solutions as well as knowledge on how to control the construction process. In this paper, we present an approach that avoids this type of rules and thus the disadvantages caused by them.We propose a static knowledge base consisting of a set of object definitions interconnected by is-a and part-of links. This conceptual hierarchy declaratively defines a taxonomy of domain objects and the aggregation of components to composite objects. Thus, the conceptual hierarchy describes the set of all admissible solutions to a constructional problem. Interdependencies between objects are represented by constraints. A solution is a syntactically complete and correct instantiation of the conceptual hierarchy.No control knowledge is included in the conceptual hierarchy. Instead, the control mechanism will use the conceptual hierarchy as a guideline. Thus it is possible to determine in which respects a current partial solution is incomplete simply by syntactical comparison with the conceptual hierarchy. The control architecture proposed here has the following characteristics: separation of control and object knowledge, declarative representation of control knowledge, and explicit control decisions in the problem solving process. Thus, a flexible control mechanism can be realized that supports interactive construction, integration of case-based approaches and simulation methods.This control method is part of an expert system kernel for planning and configuration tasks in technical domains. This kernel has been developed at the University of Hamburg and is currently applied to several domains.     

Strategic options and expert systems: a fruitful marriage

Business economics does not provide any methodology for appraising strategic investments, relying on informal approaches. Conversely, financial economics offers us plenty of sophisticated mathematical models unsuitable for applications and based on unrealistic assumptions. This paper presents an example of how strategic investments may be handled with a formal but easy-to-understand tool. While this paper shows a specific application, a real-life case, we think the model here proposed may be generalized, so contributing to developing a new approach to business decisions. In particular, we think of a fuzzy expert system approach as a convenient tool overwhelming many of the shortcomings inherent in the crisp approaches of the financial literature (DCF methods, options pricing, dynamic programming), while avoiding at the same time the refusal of any methodology (typical of business economics). The idea here presented develops some results by Magni et al. (2001) and Facchinetti et al. (2001). An evaluation function is drawn up via if-then rules; the latter are made to work automatically by means of an expert system, which adequately replicates the evaluation of human experts. A sensitivity analysis is presented to test the soundness of the model.     

Computer networks design using hybrid fuzzy expert systems

 Designing and configuring large computer networks to support a variety of applications and computational environments is difficult, as it not only requires highly specialized technical skills and knowledge, but also a deep understanding of a dynamic commercial market. Hybrid fuzzy expert systems integrate fuzzy expert systems and neural networks methods replacing classical hard decision methods and providing better performance than traditional techniques. In this paper, we present an integrated fuzzy expert system, machine learning, and neural networks approach to large structured computer networks design and evaluation. After presenting an overview of the system and the major research choices, we describe in detail the system's modules and present examples of its potential use.     

专家系统中的同步解释和驾驭推理技术研究

专家系统中的解释一般是在推理结束后把推理结果和过程显示给用户,而不能在推理的过程中同步给出解释,并让用户主动地参与到推理过程中进行共同推理。因此,提出了一种可以实现同步解释和驾驭推理的交互式推理机(IRM：Interactive Reasoning Machine)模型。在推理过程中,一方面IRM可以把推理的过程和中间结果同步地显示给用户：另一方面用户可以直接参与到推理过程中,根据当前的推理信息修改当前使用的规则和证据以完成驾驭推理.     

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.     

Categorial expert systems

Abstract: Expert systems can be used to determine some objects or consequences from uncertain knowledge by hierarchical categorization. Categorical representation is psychologically motivated and also offers an explanation of how to deal with uncertain knowledge based on counting during approximate reasoning. It is an alternative to other well‐known uncertainty calculi. A knowledge base which is used during approximate reasoning is represented by a taxonomical arrangement of verbal categories. Priming eases the formation of the final hypothesis, as more exact possible hypotheses are formed. The approximate reasoning is demonstrated on an expert system ‘Jurassic’ from the field of paleontology for the determination of a dinosaur species. It helps the paleontologist to determine creatures from uncertain knowledge. The system is composed of 423 rules arranged in a directed acyclic graph with a depth of 5. This knowledge is represented by a taxonomical arrangement of verbal categories represented by associative memories.     

Problems with expert systems in real-time control

There is increasing use of knowledge-based or expert systems in the process and manufacturing industries, with currently in excess of 2000 installations. The advantage offered by such systems is their ability to deal with complex and possibly incorrect or incomplete data. A new generation of expert-system tools, designed specifically for real-time control applications, has been developed. This paper examines the requirements of an expert system for real-time control, and shows how current approaches attempt to meet them. It is argued that none of the currently available tools fully satisfy the needs of a real-time expert control system, particularly in terms of reliability and guaranteed real-time response.     

Diagnostic expert systems: a method for engineering knowledge used in sequential diagnosis

The paper presents a method for helping knowledge engineers in modelling the knowledge involved in sequential diagnosis. In particular, we consider sequential diagnosis as a process which occurs in the following type of scenario: (1) there exist some candidate hypotheses which are to be pursued; (2) for each hypothesis there are some alternative tests which might be executed to pursue it; (3) the available knowledge about the world precludes projecting into the future (in other words, the available knowledge about the world does not afford the information needed for planning sequences of tests, i.e. for projecting the consequences of possible sequences of actions and picking the best sequence); (4) the choice of the next test (or tests) is made on the basis of the current state of knowledge; (5) the outcome of a test execution is affected by uncertainty. The suggested method addresses the problem of engineering the knowledge experts use for making decisions under uncertainty. A practical example of the method is also presented: at any time of the diagnostic process the expert is provided with a dynamically updated list of suggested tests in order to support him or her in the decision-making problem about which test to execute next.     

The rise and 'fall' of expert systems in medicine

This paper represents a personal perspective on the last 13 years of research in medical artificial intelligence and expert systems, and describes the progress of the discipline from its inception to its current status. The challenges faced by researchers are examined, and it is argued that (despite the claims) theoretical and technical limitations are not the major barriers to the successful implementation of medical artificial intelligence and expert systems, but rather more complex professional and organizational issues are at stake.     

Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems

Problems characterized by qualitative uncertainty described by expert judgments can be addressed by the fuzzy logic modeling paradigm, structured within a so-called fuzzy expert system (FES) to handle and propagate the qualitative, linguistic assessments by the experts. Once constructed, the FES model should be verified to make sure that it represents correctly the experts’ knowledge. For FES verification, typically there is not enough data to support and compare directly the expert- and FES-inferred solutions. Thus, there is the necessity to develop indirect methods for determining whether the expert system model provides a proper representation of the expert knowledge. A possible way to proceed is to examine the importance of the different input factors in determining the output of the FES model and to verify whether it is in agreement with the expert conceptualization of the model. In this view, two sensitivity and uncertainty analysis techniques applicable to generic FES models are proposed in this paper with the objective of providing appropriate tools of verification in support of the experts in the FES design phase. To analyze the insights gained by using the proposed techniques, a case study concerning a FES developed in the field of human reliability analysis has been considered.