Tools for modelling support and construction of optimization applications

We argue the case for an open systems approach towards modelling and application support. We discuss how the 'usability' and 'skills' analysis naturally leads to a viable strategy for integrating application construction with modelling tools and optimizers. The role of the implementation environment is also seen to be critical in that it is retained as a building block within the resulting system

Expert system verification concerns in an operations environment

The Space Shuttle community is currently developing a number of knowledge-based tools, primarily expert systems, to support Space Shuttle operations. It is proposed that anticipating and responding to the requirements of the operations environment will contribute to a rapid and smooth transition of expert systems from development to operations, and that the requirements for verification are critical to this transition. The paper identifies the requirements of expert systems to be used for flight planning and support and compares them to those of existing procedural software used for flight planning and support. It then explores software engineering concepts and methodology that can be used to satisfy these requirements, to aid the transition from development to operations and to support the operations environment during the lifetime of expert systems. Many of these are similar to those used for procedural hardware

The place of expert systems in a typology of information systems

This article considers definitions and claims of Expert Systems ( ES) and analyzes them in view of traditional Information systems (IS). It is argued that the valid specifications for ES do not differ fran those for IS. Consequently the theoretical study and the practical development of ES should not be a monodiscipline. Integration of ES development in classical mathematics and computer science opens the door to existing knowledge and experience. Aspects of existing ES are reviewed from this interdisciplinary point of view

Verification and validation of knowledge-based systems with an example from site selection.

In this paper, the verification and validation of Knowledge-Based Systems (KBS) using decision tables (DTs) is one of the central issues. It is illustrated using real-market data taken from industrial site selection problems.One of the main problems of KBS is that often there remain a lot of anomalies after the knowledge has been elicited. As a consequence, the quality of the KBS will degrade. This evaluation consists mainly of two parts: verification and validation (V&V). To make a distinction between verification and validation, the following phrase is regularly used: Verification deals with 'building the system right', while validation involves 'building the right system'. In the context of DTs, it has been claimed from the early years of DT research onwards that DTs are very suited for V&V purposes. Therefore, it will be explained how V&V of the modelled knowledge can be performed. In this respect, use is made of stated response modelling designs techniques to select decision rules from a DT. Our approach is illustrated using a case-study dealing with the locational problem of a (petro)chemical company in a port environment. The KBS developed has been named Matisse, which is an acronym of Matching Algorithm, a Technique for Industrial Site Selection and Evaluation.Selection; Systems;

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

The load shedding advisor: An example of a crisis-response expert system

A Prolog-based prototype expert system is described that was implemented by the Network Operations Branch of the NASA Goddard Space Flight Center. The purpose of the prototype was to test whether a small, inexpensive computer system could be used to host a load shedding advisor, a system which would monitor major physical environment parameters in a computer facility, then recommend appropriate operator reponses whenever a serious condition was detected. The resulting prototype performed significantly to efficiency gains achieved by replacing a purely rule-based design methodology with a hybrid approach that combined procedural, entity-relationship, and rule-based methods

Application of expert system techniques for award implementation

This paper describes a pilot expert system project, PESWEA, developed in conjunction with The Western Australian Government Railways Commission (Westrail), to locate and implement an expert system pilot solution to the problems and complexities of the awards. The paper will outline the process used to develop and implement a solution to a business requirement. In particular, the methodologies for the project, shell selection, and knowledge acquisition will be presented and discussed. The fundamentals of expert systems will be discussed to provide the reader an insight into the technology. In addition, this paper reviews the literature relevant to the research questions. Empirical findings in the literature are discussed and analysed to discover how they influence the work in this paper. The topics covered include the concepts of expert system shell selection, knowledge acquisition and representation. and the integration of expert systems and database systems. A case study on a similar pilot system conducted by the State Electricity Commission of Victoria (SECV) is also reviewed. The PESWEA knowledge-bases were implemented with the 1st-Class HT expert system shell which succeeded in meeting the selection criteria for the first study in this project. The work carried out has also confirmed that the expert system techniques can be used to gather and interpret information from manual time- sheets which are subject to a complex arbitration award. Furthermore, PESWEA utilised the Inter-system Communication approach to systems interfacing, with the DataFlex database system dominating the concentration of processing and control. The technical and business objectives of PESWEA have been achieved with success. This study has confirmed SECV\u27s own research into the applicability of expert system techniques for award implementation. From this study, Westrail and Edith Cowan University believe that expert systems technology can now be integrated into the mainstream programming techniques at Westrail

Development of an intelligent hypertext manual for the space shuttle hazardous gas detection system

A computer-based Integrated Knowledge System (IKS), the Intelligent Hypertext Manual (IHM), is being developed for the Space Shuttle Hazardous Gas Detection System (HGDS) at the Huntsville Operations Support Center (HOSC). The IHM stores all HGDS related knowledge and presents them in an interactive and intuitive manner. The IHM's purpose is to provide HGDS personnel with the capabilities of: enhancing the interpretation of real time data; recognizing and identifying possible faults in the Space Shuttle sub-system related to hazardous gas detections; locating applicable documentation related to procedures, constraints, and previous fault histories; and assisting in the training of personnel

Modelling decision tables from data.

On most datasets induction algorithms can generate very accurate classifiers. Sometimes, however, these classifiers are very hard to understand for humans. Therefore, in this paper it is investigated how we can present the extracted knowledge to the user by means of decision tables. Decision tables are very easy to understand. Furthermore, decision tables provide interesting facilities to check the extracted knowledge on consistency and completeness. In this paper, it is demonstrated how a consistent and complete DT can be modelled starting from raw data. The proposed method is empirically validated on several benchmarking datasets. It is shown that the modelling decision tables are sufficiently small. This allows easy consultation of the represented knowledge.Data;

Building Credit-Risk Evaluation Expert Systems Using Neural Network Rule Extraction and Decision Tables.

In this paper, we evaluate and contrast four neural network rule extraction approaches for credit scoring. Experiments are carried out on three real life credit scoring data sets. Both the continuous and the discretised versions of all data sets are analysed. The rule extraction algorithms, Neurolinear, Neurorule, Trepan and Nefclass, have different characteristics with respect to their perception of the neural network and their way of representing the generated rules or knowledge. It is shown that Neurolinear, Neurorule and Trepan are able to extract very concise rule sets or trees with a high predictive accuracy when compared to classical decision tree (rule) induction algorithms like C4.5(rules). Especially Neurorule extracted easy to understand and powerful propositional ifthen rules for all discretised data sets. Hence, the Neurorule algorithm may offer a viable alternative for rule generation and knowledge discovery in the domain of credit scoring.Credit; Information systems; International; Systems;