• Journal of Biosystems Engineering
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• v.18 no.2
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• pp.133-143
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• 1993

In developing an Expert System(ES), there are two ways. One is to develop an ES using AI(artificial Intelligence) languages and another using ES-development tools. CLIPS is an ES-development tool and has a powerful inference engine in it. Using the tool like CLIPS, knowledge engineer can concentrate on constructing a knowledge base without wasting time in developing an inference engine. However, CLIPS is lack of user-friendly interfaces for both knowledge enginners and users. Because CLIPS was developed in USA, it can not afford to use Korean language. Therefore, several user-friendly interfaces including hmenu, htille, hpcxdisplay were develpoed and added to CLIPS. CLIPS with the interfaces is called HCLIPS(Hangul CLIPS) in this paper. HCLIPS provides a new I/O device to be utilized for expert systems in Korean. HCLIPS can be efficiently used for developing expert systems in agriculture and consulting farmers interactively who are not familiar with computer programming and ES itself.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.363-371
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• 1994

This thesis investigates an expert system(ES) to propose fault restoration plan by utilizing tree search strategies. In order to cope with an extensive amount of data and frequent breaker switching operations in distribution systems, the database of system configuration is constructed by using binary trees. This remarkably enhances the efficiency of search algorithm and makes the proposed ES easily adaptable to system changes due to switching operations. The rule-base is established to fully utilize the meris of tree-structured database. The inferring strategy is developed mainly based on the best-first search algorithm to increase computation efficiency. The proposed ES has been implemented to efficiently deal with large distribution systems by reducing computational burden remarkably compared with the conventional ES's.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.10
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• pp.149-156
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• 2010

In this paper, the optimal design of a wind generator, implemented with the hybridized GA(Genetic Algorithm) and ES(Expert System), has been performed to maximize the AEP(Annual Energy Production) over the whole wind speed characterized by the statistical model of wind speed distribution. In particular, to solve the problem of calculation iterate, ES finds the superior individual and apply to initial generation of GA and it makes reduction of search domain. Meanwhile, for effective searching in reduced search domain, it propose Intelligent GA algorithm. Also, it shows the results of optimized model 500[kW] wind generator using hybridized algorithm and benchmark result of compare with GA.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.679-684
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• 1996

The work was aimed at realize the problem of seed processing . Solving this problem it was ascertained that the existing mathematical methods are reliable enough, but they are used practically very seldom. The work offers to use the expert system technology which allows to solve problems connected with practical knowledge of experts in the region of investigation effectively. The method of knowledge structuring and analizing as well as technique of knowledge acquisition which is necessary for realization of this technology are worked-out in the work. As the result applying the worked-out method the prototypes of the expert system (ES) are created : -ES " Sieves " ; research prototype for the sieve choice for the seed sorting machines -ES " Diagnostics " ; displaying prototype for the technological determination of action disrepair of seed sorting machines.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.568-571
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• 2004

In this study, we propose an efficient expert system (ES) construction mechanism by using dynamic knowledge map (DKM) and database management systems (DBMS). Generally, traditional ES and ES developing tools has some limitations such as, 1) a lot of time to extend the knowledge base (KB), 2) too difficult to change the inference path, 3) inflexible use of inference functions and operators. First, to overcome these limitations, we use DKM in extracting the complex relationships and causal rules from human expert and other knowledge resources. Then, elation database (RDB) and its management systems will help to transform the relationships from diagram to relational table. Therefore, our mechanism can help the ES or KBS (Knowledge-Based Systems) developers in several ways efficiently. In the experiment section, we used medical data to show the efficiency of our mechanism. Experimental results with various disease show that the mechanism is superior in terms of extension ability and flexible inference.

• Journal of Korean Society for Quality Management
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• v.16 no.2
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• pp.34-47
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• 1988

Decision support system (DSS) has been expected to be a powerful tool for aiding the decision making processes in business organizations. But it's contribution has turned to be somewhat doubtful, In this paper, an intergrated systems design apporach is suggested, which integrates DSS and expert system (ES) for the enhancement of performance of DSS, after carefully reviewing both DSS and ES.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.337-340
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• 1991

The most difficult, time-consuming, and expensive task in building an ES (Expert System) is constructing and debugging its knowledge base. Our goals are to eliminate the knowledge-acquisition bottle-neck for ES creation in data rich situations and to make an ANN (Artificial Neural Network) model behave as much as possible like an ES. The ANN ES has many benifits: Once it has been learned, inference time is very short. It can provide a reasonable conclusion for insufficient input data. But it has also several demerits : Learning time is too long to converge. We cannot guarantee the convergence of its weights. We introduce an ANN ES model which makes most of its benefits and compensates its shortcomings.

• Asia pacific journal of information systems
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• v.6 no.1
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• pp.75-108
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• 1996

Expert Systems (ES) have been successfully applied to bank loan decisions. However, with regard to bank loan decisions, most loan officers approach the acquisition of an ES with apprehension, which implies that organizational resources devoted to the development and implementation of ES may have been wasted or misused. Because the primary cause of the users resistance to use ES are more significantly related to the behavioral elements rather than technical elements, applying appropriate behavioral theory to the well representative sample group of the whole bank loan officers in the United States with a very accurate measurement tool can provide some clues for developing successful ES for bank loan officers. In this study : 1) Vroom's (1964) expectancy theory was selected to explain bank loan managers' motivation to use an ES ; and 2) the ANN model's prediction power to estimate bank loan officers' motivation levels of using an ES was examined.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.128-130
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• 1993

In this paper, we introduce 'Expert System(ES)' for Fault Diagnosis(FD) in unmanned-Substation(S/S). In contrast with the co nventional ES, this ES has the following characteristics. First, this ES performs the function that judges the right or false operation of Relays(Ry's) and Circuit Breakers(CB's) in S/S. Then, with this information of the above judgments and the operating times of Ry's and CB's, the candidates of the feasible fault areas are generated. Several examples are presented to show the validity of this system.

• Korean Management Science Review
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• v.2
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• pp.26-38
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• 1985

전문가 체제 (Expert System: 이하 ES라 부름)란 회귀하고 값비싼 전문가의 지식과 경험을 체계화하여 콤퓨터에 기억시켜 둠으로써 전문가가 아닌 많은 사람들이 전문가를 만나지 않고서도 ES를 통하여 전문가의 능력을 빌릴 수 있도록 한 것이다. 전문가 체제는 오래전부터 콤퓨터 전문가들의 연구 분야였던 인공지능(Artificial Intelligence)을 그 모체로 하고 있으나 최근에는 경영정보체제(Management Information System)나 의사결정 지원체제 (Decision Support System)분야에 종사하는 분들의 ES에 대한 관심이 날로 증가하고 있다.(중략)