The subject of this thesis is the development of an expert system to offer advising for variance reduction technique (VRT) selection in simulation. Simulation efficiency is increased by appropriate use of variance reduction techniques. The process of selecting VRTs brings a sharper focus to issues of experimental design and thus to the very purpose and objectives to be attained by the simulation. Students in the University of Arizona Systems and Industrial Engineering Department graduate courses are the intended users of this expert system, with the expectation that their practice of simulation will be facilitated.

The current generation of conventional software productivity tools is likely to achieve at most a factor of two reduction in life-cycle costs by the early 1990s. With projected order of magnitude increases in system complexity and size, a far greater improvement (factor of 10 or higher) is needed. Significant cost reductions and qualitative improvements for many kinds of applications can be demonstrated by means of a knowledge-based integrated tool environment that both adheres to the software development standards of the software development organization and promotes rapid development of high quality knowledge-based systems and their integration within highly specialized application environmentsThis investigation has led to the construction of the (K)nowledge (I)ntegration (T)ool, an operational testbed and architectural framework for the rapid development of highly extensible artificial intelligence systems and environments that both support the conventional life-cycle paradigm and facilitate the evolution of a knowledge-based life-cycle paradigm. A knowledge-based system is a programming system characterized by the ease with which objects, the relationships between them, and higher-level concepts composed of such objects and relationships, are manipulated and presented graphically and textually. The KIT consists of: knowledge-based integrated tool environments, integrated assemblages of knowledge-based systems that possess a man-machine interface that adjusts to the needs of individual users by means of user-profile and application-specific information; and a knowledge-based based system development environment, a knowledge-based system that supports the construction and maintenance of software systems, and acts as a mechanism to improve the reliability of the software development process. This thesis describes the synthesis of these system types in the KIT.Following the KIT's successful prototyping and demonstration, it is being scaled up and incrementally developed to provide life-cycle automation capabilities for a roboticized factory of a major aerospace company. In this thesis the historical and theoretical foundations, capabilities, current and planned uses of the KIT are described.Key Words: Artificial Intelligence, Knowledge Base, Life-cycle Automation, Knowledge-Based Environment, Knowledge-Based Systems, Knowledge-Based Project Management, Knowledge-Based Configuration Management, Knowledge-Based System Development, Knowledge-Based Software Engineering. / Department of Computer Science

No description available.

This thesis focuses on the explanation of anomalies as an approach to anomaly-driven revision of a theory. An anomaly is identified when a theory (or model of a domain) does not accurately reflect a domain observation, indicating that the theory (or model) requires refinement. In some cases an explanation can be generated for an anomalous observation using existing domain knowledge and hence a revision to the existing theory can be provided. Ontologies have been used in both stages of an investigation presented in this thesis; in the first stage, a domain ontology and expert-acquired strategies have been used as part of a knowledge-based system, EIRA (Explaining, Inferencing, and Reasoning about Anomalies), to generate explanations for an anomaly; in the second stage, domain ontologies have been used to suggest refinements to an incorrect or incomplete domain ontology. In the first stage of the investigation, extensive interviews were held with domain experts; the analysis of which led to the identification of both examples of anomalies encountered in the domain and the strategies used by the domain experts to provide (appropriate) explanations for the anomalies. EIRA is able to replicate these explanations; when EIRA is presented with an anomaly, potential explanations are generated by the application of expert-acquired strategies to the domain knowledge, patient data, and information about the clinical situation. To evaluate this approach, EIRA has been applied in the Intensive Care Unit (ICU) domain and ICU clinicians have evaluated the explanations produced by EIRA. The strategies used by EIRA have been abstracted further to form generic strategies for anomaly resolution. In the second stage, EIRA has been extended to investigate the use of domain ontologies to suggest refinements to an incomplete or incorrect ontology. These additional refinements are generated by reasoning about analogous concepts from the domain ontology. The findings described in this thesis support the belief that ontologies can be used to generate explanations to refine a theory, further, that the extensive domain knowledge contained in an ontology allows for sophisticated refinements of a knowledge base. Previous approaches to theory revision have largely focused on the refinement of an instantiated rule base, in which limited domain knowledge is incorporated in the rules and hence the refinements are essentially captured in a particular knowledge base. In these earlier approaches, refinements to remove the anomaly were generally suggested after applying machine learning techniques on data from the domain; however, this process requires large datasets, the refinements generated are not always acceptable to domain experts, and providing explanations (using an ontology) to account for anomalies have not been investigated. I believe that the findings reported in this thesis are significant and make a number of contributions including a novel approach to anomaly-driven revision of a theory.

The Armed Forces of the United States are becoming more expeditionary in nature, in that more forces will be home-ported or home-stationed in the Continental U.S. One of the major characteristics associated with future military concepts is that they employ Joint and Coalition Forces from a sea base conducting a full range of operations in the littoral regions of the world. A key aspect of conducting operations is the sustainment of forces in a sea based environment. Future logistical architectures associated with providing that sustainment will be joint and integrated to provide seamless support to all forces operating in and around the sea base. The ordering system associated with that future logistical architecture must be robust, redundant, and not have a single point of failure. The ordering and tracking of all sustainment supplies through the supply chain distribution system will be important in ensuring that supplies are delivered to the right place and time to guarantee success. This thesis proposes to emphasize a functional architecture for an Expert Ordering System in a Sea Based environment that will reduce the overall logistical manpower requirements of the Joint/Combined Force. Use cases of different realistic scenarios will be produced to show justification of the system.

Large areas of the UK have witnessed intense industrialisation since the industrial revolution in the latter part of the 18th Century. Increased environmental awareness and pressure to redevelop brown field sites, have resulted in the majority of civil engineering projects undertaken within the UK encountering some form of contamination. In order to collect the vast amount of information required to assess a potentially contaminated site, a multi-stage site investigation (preliminary investigation, exploratory and detailed investigation) is usually undertaken. The information collected during the investigation allows the three components of the risk assessment process to be identified. These components are the source of contamination, possible pathways for the movement of contaminants and vulnerable targets on and off site. A prototype knowledge-based system (ATTIC Assessment Tool for The Investigation of Contaminated Land) has been developed to demonstrate that knowledge-based technology can be applied to the preliminary stage of the investigation of contaminated land. ATTIC assesses information collected during the preliminary stage of an investigation (past use, geological map, hydrological maps etc.) and assists with the risk assessment process, with the prediction of potential contaminants, hazards and risk to neighbouring areas. The system has been developed, using CLIPS software. It consists of four knowledgebases (source, pathway, target and health and safety knowledge-base), containing 1600 rules. The knowledge within the knowledge-bases was obtained from two main sources. The initial and main source was the technical literature. Obtaining knowledge from technical literature involved reviewing published material, extracting relevant information and converting information into rules suitable for the knowledge-base system. The second source of knowledge was domain experts via a knowledge elicitation exercise. The exercise took the form of a questionnaire relating to the rules and parameters within the system. A Visual Basics interface was also developed in conjunction with the knowledge-based system, in order to allow data entry to the system. The interface uses a series of forms relating to different components within the risk assessment process. On completion of compiling the prototype, the system was validated against a number of case studies. The system predicted the likely contaminants with a reasonable match to those observed, even though the input data for the case studies was limited. The assessment of risks to neighbouring target areas was generally in agreement with the case study reports, matching similar risk values and directions. In addition to the development of the prototype system, a database modelled on the Association of Geotechnical Specialists electronic format for the transfer of ground investigation data was also developed to store preliminary investigation information. The data structures were implemented using Microsoft Access relational database management system software. This allowed the database to be developed within a Microsoft Windows environment.

Call number: LD2668 .T4 1986 F63 / Master of Science / Computing and Information Sciences

by Hung Cheung Kwok. / Thesis (M.S.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves [34]). / ACKNOWLEDGEMENTS / ABSTRACT / TABLE OF CONTENTS / Chapter 1. --- INTRODUCTION --- p.3 / Chapter 1.1 --- PROVISION OF NETWORK SERVICES --- p.3 / Chapter 1.2 --- THE CURRENT ENVIRONMENT FOR SERVICE PROVISION --- p.3 / Chapter 1.3 --- THE COMING ENVIRONMENT FOR SERVICE PROVISION --- p.6 / Chapter 1.4 --- THE ROLE OF THE ASSISTANT SYSTEM --- p.8 / Chapter 1.5 --- OVERVIEW OF THE THESIS --- p.10 / Chapter 2 . --- OVERALL DESIGN --- p.12 / Chapter 2.1 --- INFERENCE ENGINE --- p.14 / Chapter 2 .2 --- KNOWLEDGE BASES --- p.14 / Chapter 2.3 --- COMMAND GENERATOR --- p.15 / Chapter 2.4 --- USER INTERFACE --- p.16 / Chapter 2.5 --- HOST INTERFACE --- p.16 / Chapter 3 . --- KNOWLEDGE BASE DESIGN --- p.18 / Chapter 4. --- INFERENCE ENGINE DESIGN --- p.21 / Chapter 5. --- IMPLEMENTATION --- p.24 / Chapter 5.1 --- SYSTEM DESIGN --- p.24 / Chapter 5.2 --- KNOWLEDGE BASE MAINTENANCE --- p.24 / Chapter 5.3 --- MANUAL MODE --- p.26 / Chapter 5.4 --- AUTOMATIC MODE --- p.27 / Chapter 5.5 --- INTERFACE FUNCTIONS --- p.29 / Chapter 6. --- CONCLUSIONS --- p.31 / REFERENCES / LIST OF FIGURES / Chapter F1. --- THE SCHEMATICS OF THE INTELLIGENT SYSTEM / LIST OF TABLES / Chapter T1. --- STRUCTURE OF SERVICE INFORMATION FILE (SIF) / Chapter T2. --- STRUCTURE OF WORK CODE FILE (WCF) / Chapter T3. --- STRUCTURE OF MAPPING FILE (SIF-PRF´ØMAP) / Chapter T4. --- DATABASE RECORDS OF SIF一PRF.MAP / APPENDICES / Chapter A1. --- KNOWLEDGE BASE LIST FOR FEATURE ANALYSIS (CHK_SIF) / Chapter A2. --- KNOWLEDGE BASE LIST FOR WORK CODE INTERPRETATION (CHK一WCF) / Chapter A3. --- KNOWLEDGE BASE LIST FOR FILE SENDING MONITORING (CHK 一SND) / Chapter A4. --- A SAMPLE RUN OF THE SYSTEM

by Chang Yu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 111-115). / Acknowledgement --- p.i / Abstract --- p.ii / List of Tables --- p.vii / List of Figures --- p.viii / Chapter 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- Motivation and Objectives --- p.1 / Chapter 1.2 --- Outline of the Work of This Thesis --- p.4 / Chapter 1.3 --- Organization of the Thesis --- p.5 / Chapter 2 --- REVIEW OF RELATED WORKS --- p.6 / Chapter 2.1 --- Deduce2 --- p.6 / Chapter 2.2 --- ARES --- p.8 / Chapter 2.3 --- VAGUE --- p.10 / Chapter 2.4 --- Fuzzy Sets-Based Approaches --- p.12 / Chapter 2.5 --- Some General Remarks --- p.14 / Chapter 3 --- A FUZZY DATABASE QUERY LANGUAGE --- p.18 / Chapter 3.1 --- Basic Concepts of Fuzzy Sets --- p.18 / Chapter 3.2 --- The Syntax of the Fuzzy Query Language --- p.21 / Chapter 3.3 --- Fuzzy Operators --- p.25 / Chapter 3.3.1 --- AND --- p.27 / Chapter 3.3.2 --- OR --- p.27 / Chapter 3.3.3 --- COMB --- p.28 / Chapter 3.3.4 --- POLL --- p.28 / Chapter 3.3.5 --- HURWICZ --- p.30 / Chapter 3.3.6 --- REGRET --- p.31 / Chapter 4 --- SYSTEM DESIGN --- p.35 / Chapter 4.1 --- General Requirements and Definitions --- p.35 / Chapter 4.1.1 --- Requirements of the system --- p.36 / Chapter 4.1.2 --- Representation of membership functions --- p.38 / Chapter 4.2 --- Overall Architecture --- p.41 / Chapter 4.3 --- Interface --- p.44 / Chapter 4.4 --- Knowledge Base --- p.46 / Chapter 4.5 --- Parser --- p.51 / Chapter 4.6 --- ORACLE --- p.52 / Chapter 4.7 --- Data Manager --- p.53 / Chapter 4.8 --- Fuzzy Processor --- p.57 / Chapter 5 --- IMPLEMENTION --- p.59 / Chapter 5.1 --- Some General Considerations --- p.59 / Chapter 5.2 --- Knowledge Base --- p.60 / Chapter 5.2.1 --- Converting a concept into conditions --- p.60 / Chapter 5.2.2 --- Concept trees --- p.62 / Chapter 5.3 --- Data Manager --- p.64 / Chapter 5.3.1 --- Some issues on the implementation --- p.64 / Chapter 5.3.2 --- Dynamic library --- p.67 / Chapter 5.3.3 --- Precompiling process --- p.68 / Chapter 5.3.4 --- Calling standard --- p.71 / Chapter 6 --- CASE STUDIES --- p.76 / Chapter 6.1 --- A Database for Job Application/Recruitment --- p.77 / Chapter 6.2 --- Introduction to the Knowledge Base --- p.79 / Chapter 6.3 --- Cases --- p.79 / Chapter 6.3.1 --- Crispy queries --- p.79 / Chapter 6.3.2 --- Fuzzy queries --- p.82 / Chapter 6.3.3 --- Concept queries --- p.85 / Chapter 6.3.4 --- Fuzzy Match --- p.87 / Chapter 6.3.5 --- Fuzzy operator --- p.88 / Chapter 7 --- CONCLUSION --- p.93 / Appendix A Sample Data in DATABASE --- p.96 / Bibliography --- p.111

by C.H. Fung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1989. / Bibliography: leaves [81-82]