PERSONEL SEÇİM SÜRECİNDE UZMAN SİSTEM YAKLAŞIMI VE KONYA BÜYÜKŞEHİR BELEDİYESİNDE BİR UYGULAMA

Bu çalışmada, yapay zekanın bir alt disiplini olan uzman sistemler US incelenmişve personel seçimine yönelik “Expert-Personel” adında bir uzman sistem geliştirilmiştir. Sistem, Konya Büyükşehir Belediyesinde, Belediye Başkan Yardımcısı, Çevre Koruma Daire Başkanıve Çevre Şube Müdürü seçimine yönelik olarak uygulanmıştır. Bu birimler için işanalizi ve görev tanımlarıyapıldıktan sonra uygun bir işbaşvuru formu oluşturulmuştur. Ayrıca adayların kişilik özelliklerini belirlemeye yönelik kişilik belirleme sorularıoluşturulmuşve en uygun adaylar “Expert-Personel” uzman sistemi yardımıile belirlenmiştir

A machine learning approach to automated construction of knowledge bases for expert systems for remote sensing image analysis with GIS data

Knowledge-based remote sensing image analysis with GIS data is acknowledged as a promising technique. However, the difficulty in knowledge acquisition, a well-known bottleneck in building knowledge-based systems, impedes the adoption of this technique. Automating knowledge acquisition is therefore in demand. This paper presents a machine learning approach to automated construction of knowledge bases for image analysis expert systems integrating remotely sensed and GIS data. The methodology applied in the study is based on inductive learning techniques in machine learning, a subarea of artificial intelligence. It involves training with examples from remote sensing and GIS data, learning using the inductive principles, decision tree generating, rule generating from the decision tree, and knowledge base building for an image analysis expert system. This method was used to construct a knowledge base for wetland classification of Par Pond on the Savannah River Site, SC, using SPOT image data and GIS data. The preliminary results show that this method can provide an effective approach to integration of remotely sensed and GIS data in geographic information processing

Knowledge and model based reasoning for power system protection performance analysis

Technological advances within the field of power systems has led to engineers, at all levels, being confronted with an ever increasing amount of data to be analysed. This coincides with greater pressure on engineers to work more efficiently and cost effectively, due to the increasingly competitive nature of the electricity supply industry. As a result, there is now the requirement for intelligent systems to interpret the available data and provide information which is relevant, manageable and readily assimilated by engineers. This thesis concerns the application of intelligent systems to the data interpretation tasks of protection engineers. An on-line decision support system is discussed which integrates two expert system paradigms in order to perform power system protection performance analysis. Knowledge based system techniques are used to interpret the data from supervisory, control and data acquisition systems, whereas a model based diagnosis approach to the comprehensive validation of protection performance, using the more detailed data which is available from fault records or equivalent, is assessed. Such a decision support system removes the requirement for time consuming manual analysis of data. An assessment of power system protection performance is provided in an on-line fashion, quickly alerting the engineers to failures or problems within the protection system. This improves efficiency and maximises the benefit of having an abundance of data available.Technological advances within the field of power systems has led to engineers, at all levels, being confronted with an ever increasing amount of data to be analysed. This coincides with greater pressure on engineers to work more efficiently and cost effectively, due to the increasingly competitive nature of the electricity supply industry. As a result, there is now the requirement for intelligent systems to interpret the available data and provide information which is relevant, manageable and readily assimilated by engineers. This thesis concerns the application of intelligent systems to the data interpretation tasks of protection engineers. An on-line decision support system is discussed which integrates two expert system paradigms in order to perform power system protection performance analysis. Knowledge based system techniques are used to interpret the data from supervisory, control and data acquisition systems, whereas a model based diagnosis approach to the comprehensive validation of protection performance, using the more detailed data which is available from fault records or equivalent, is assessed. Such a decision support system removes the requirement for time consuming manual analysis of data. An assessment of power system protection performance is provided in an on-line fashion, quickly alerting the engineers to failures or problems within the protection system. This improves efficiency and maximises the benefit of having an abundance of data available

GUIDELINES FOR THE DESIGN OF ENHANCED, COST EFFECTIVE NETWORKS IN A MANUFACTURING ENVIRONMENT

Investigations into the transmission of real-time interactive speech over local area networks (LAN) in an industriai/commerciai environment to eventually obviate the need for a private automatic branch exchange and ultimately prepare the way for a single interactive integrated information system (PS) that provides work stations, which are networked via a LAN, with a fully interactive speech and graphics facility commensurate with the future requirements in computer integrated manufacturing (CIM). The reasons for conducting this programme of research were that existing LANs do not offer a real time interactive speech facility. Any verbal communication between workstation users on the LAN has to be carried out over a telephone network (PABX). This necessitates the provision of a second completely separate network with its associated costs. Initial investigations indicate that there is sufGcient capacity on existing LANs to support both data and real-time speech provided certain data packet delay criteria can be met. Earlier research work (in the late 1980s) has been conducted at Bell Labs and MIT. [Ref 25, 27 & 28], University of Strathclyde [Ref 24] and at BTRL [Ref 22 and 37]. In all of these cases the real time implementation issues were not fijlly addressed. In this thesis the research work reported provides the main criteria for the implementation of real-time interactive speech on both existing and newly installed networks. With such enhanced communication facilities, designers and engineers on the shop floor can be projected into their suppliers, providing a much greater integration between manufacturer and supplier which will be beneficial as Concurrent and Simultaneous Engineering Methodologies are further developed. As a result, various LANs have been evaluated as to their suitability for the transmission of real time interactive speech. As LANs, in general, can be separated into those with either deterministic or stochastic access mechanisms, investigations were carried out into the ability of both the: (i) Token Passing Bus LANs supporting the Manufacturing and Automation Protocol (MAP)—Deterministic and (u) Carrier Sense Multiple Access/Collision Detection (CSMA/CD) LANs supporting the Technical Office Protocol (TOP)— Stochastic to support real time interactive speech, as both are used extensively in commerce and manufacturing. The thesis that real time interactive speech can be transmitted over LANs employed in a computer integrated manufacturing environment has to be moderated following the tests carried out in this work, as follows:- The Token Passing LAN presents no serious problems under normal traffic conditions, however, the CSMA/CD LAN can only be used in relatively light traffic conditions i.e. below 30% of its designed maximum capacity, providing special arrangements are made to minimise the access, transmission and processing delays of speech packets. Given that a certain amount of delay is inevitable in packet switched systems (LANs), investigations have been carried out into techniques for reducing the subjective efifect of speech packet loss on real-time interactive systems due to the unacceptable delays caused by the conditions mentioned above

Meta-level argumentation framework for representing and reasoning about disagreement

The contribution of this thesis is to the field of Artificial Intelligence (AI), specifically to the sub-field called knowledge engineering. Knowledge engineering involves the computer representation and use of the knowledge and opinions of human experts.In real world controversies, disagreements can be treated as opportunities for exploring the beliefs and reasoning of experts via a process called argumentation. The central claim of this thesis is that a formal computer-based framework for argumentation is a useful solution to the problem of representing and reasoning with multiple conflicting viewpoints.The problem which this thesis addresses is how to represent arguments in domains in which there is controversy and disagreement between many relevant points of view. The reason that this is a problem is that most knowledge based systems are founded in logics, such as first order predicate logic, in which inconsistencies must be eliminated from a theory in order for meaningful inference to be possible from it.I argue that it is possible to devise an argumentation framework by describing one (FORA : Framework for Opposition and Reasoning about Arguments). FORA contains a language for representing the views of multiple experts who disagree or have differing opinions. FORA also contains a suite of software tools which can facilitate debate, exploration of multiple viewpoints, and construction and revision of knowledge bases which are challenged by opposing opinions or evidence.A fundamental part of this thesis is the claim that arguments are meta-level structures which describe the relationships between statements contained in knowledge bases. It is important to make a clear distinction between representations in knowledge bases (the object-level) and representations of the arguments implicit in knowledge bases (the meta-level). FORA has been developed to make this distinction clear and its main benefit is that the argument representations are independent of the object-level representation language. This is useful because it facilitates integration of arguments from multiple sources using different representation languages, and because it enables knowledge engineering decisions to be made about how to structure arguments and chains of reasoning, independently of object-level representation decisions.I argue that abstract argument representations are useful because they can facilitate a variety of knowledge engineering tasks. These include knowledge acquisition; automatic abstraction from existing formal knowledge bases; and construction, rerepresentation, evaluation and criticism of object-level knowledge bases. Examples of software tools contained within FORA are used to illustrate these uses of argumentation structures. The utility of a meta-level framework for argumentation, and FORA in particular, is demonstrated in terms of an important real world controversy concerning the health risks of a group of toxic compounds called aflatoxins

Inference engine in objectbase: a mean towards metasystems.

Yu-shan Chan.Thesis (M.Phil.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 95-99).Chapter 1. --- INTRODUCTION --- p.1Chapter 1.1 --- "Expert System, Expert System Shell, and ""MetaSystem""" --- p.2Chapter 1.2 --- Adopting OBJECTBASE In EXPERT SYSTEM SHELL(ESS) --- p.4Chapter 2. --- SURVEY ON EXISTING SYSTEMS --- p.7Chapter 2.1 --- Review of inference models --- p.7Chapter 2.1.1 --- The Classical Period --- p.9Chapter 2.1.2 --- The modern period --- p.11Chapter 2.2 --- Rules in Objectbase vs. other Representations --- p.12Chapter 2.2.1 --- Rule-based systems --- p.13Chapter 2.2.2 --- Object-oriented systems --- p.13Chapter 2.2.3 --- Other systems --- p.13Chapter 2.2.4 --- Rules embedded in object-- the Objectbase approach --- p.14Chapter 2.3 --- Conclusion --- p.15Chapter 3. --- DESIGN OF ESS FOR AN OBJECTBASE SYSTEM --- p.16Chapter 3.1 --- Introducing ESS in Objectbase --- p.18Chapter 3.1.1 --- The Concept of Object Modeling --- p.19Chapter 3.1.2 --- Why Objectbase? --- p.20Chapter 3.1.3 --- ESS : a higher layer on Objectbase --- p.22Chapter 3.1.4 --- Schema Objects and Shell Objects --- p.23Chapter 3.2 --- Module design of ESS --- p.24Chapter 3.2.1 --- Knowledge Representation Module --- p.25Chapter 3.2.2 --- Objectbase inference module --- p.27Chapter 3.2.3 --- The Rule一Inference Module --- p.28Chapter 3.3 --- Knowledge Representation --- p.29Chapter 3.3.1 --- Schema Knowledge & the Rulebase --- p.30Chapter 3.3.2 --- Rule Structure --- p.31Chapter 3.4 --- Inference Engine --- p.35Chapter 3.4.1 --- The Two Levels of Inference --- p.35Chapter 3.5 --- Rule一Inference (RI) --- p.37Chapter 3.5.1 --- Structural design of RI --- p.38Chapter 3.5.2 --- Drawing Inference --- p.39Chapter 3.5.3 --- Query Processor and RI --- p.42Chapter 3.5.4 --- RI and the Inference Engine(IE) --- p.43Chapter 3.6 --- Conclusion --- p.43Chapter 4. --- IMPLEMENTATION --- p.45Chapter 4.1 --- Rulelnference: a comprehensive structure --- p.46Chapter 4.1.1 --- Class Rule --- p.46Chapter 4.1.2 --- Class RuleList --- p.47Chapter 4.1.3 --- Accompany data structures for inference --- p.48Chapter 4.1.4 --- Class Rulelnference --- p.49Chapter 4.2 --- Rule Setting --- p.51Chapter 4.2.1 --- Rule Construction --- p.51Chapter 4.2.2 --- Rule Parsing and the Rule Definition Language (RDL) --- p.52Chapter 4.3 --- How Inference is done in ESS --- p.53Chapter 4.3.1 --- Reset and Load system --- p.53Chapter 4.3.2 --- Inference making --- p.54Chapter 4.4 --- Using RuleInference in the Rule Constructor --- p.58Chapter 4.4.1 --- The Rule Constructor --- p.59Chapter 4.5 --- Using Rulelnference in the Application Constructor --- p.60Chapter 4.5.1 --- The RiNode --- p.61Chapter 4.5.2 --- Schema and Rule Set Handling --- p.63Chapter 4.6 --- Conclusion --- p.64Chapter 5. --- CASE STUDY --- p.66Chapter 5.1 --- Background on Statement analysis --- p.66Chapter 5.1.1 --- Ratios for decision making --- p.68Chapter 5.2 --- Sample System: Financial Data Analysis System --- p.70Chapter 5.2.1 --- The FINANCE schema --- p.71Chapter 5.2.2 --- Rules --- p.73Chapter 5.2.3 --- Results --- p.75Chapter 5.3 --- Evaluation --- p.81Chapter 5.4 --- Conclusion --- p.82Chapter 6. --- RESULT AND DISCUSSION --- p.84Chapter 6.1 --- An Expert System Shell on Objectbase --- p.84Chapter 6.2 --- The ESS on MOBILE --- p.85Chapter 6.3 --- Pros and cons for the ESS --- p.86Chapter 6.4 --- MOBILE: how it has been improved --- p.87Chapter 7. --- CONCLUSION --- p.89Chapter 7.1 --- Comparison --- p.91Chapter 7.2 --- Appraisal --- p.92Chapter 8. --- REFERENCES --- p.95Table of Content for AppendixesAPPENDIX 1. RULE DEFINITION LANGUAGE --- p.100APPENDIX 2. THE CLASS RULEINFERENCE --- p.103APPENDIX 3. THE RINODE --- p.104APPENDIX 4. FINANCIAL STATEMENT ANALYSIS --- p.108APPENDIX 5. DATA STRUCTURE OF RULE AND RULELIST --- p.117APPENDIX 6. DATA STRUCTURE OF VARLIST AND ACTLIST --- p.118APPENDIX 7. DATA STRUCTURE OF RULEINFERENCE --- p.12