• 대한한의진단학회지
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• 제12권2호
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• pp.107-126
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• 2008

Background : There was seldom study about method that diagnose 8 Constitution beside method of pulse diagnosis in 8 Constitution Medicine. Objectives : This study is to make out 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning). Methods : First, at case base construction process we constructed case base for CBR embodiment because gathering 925 cases all to patient who constitution is verified, and second, at study model establishment process superior expert system development by purpose CBR of reasoning process dividing fundamental type CBR that spend basis data value and expert type CBR that reflect weight in basis data value accordin I II III to advice expert opinion, and third, system embodiment process explained about way to give process and weight that diagnose constitution through Nearest Neighbor Method sampling process of CBR techniques, and fourth, at system estimation process we selected superior CBR model because comparing and estimate the diagnosis rate of expert system with fundamental type system (GECBR) model and expert type I II III CBR system (AVCBR, AACBR, AGCBR) model that reflect expert opinion in fundamental type system. GECBR and AGCBR chose on superior study model. Through such 4 study process, we developed 8 constitution diagnosis expert system lastly. Results : 1. When we select GECBR that is fundamental type by reasoning system, diagnosis rate 78.91% of 8 constitution diagnosis expert system is expected, and the constitution diagnosis rate Hepatonia 90.4%, Cholecystonia 63.0%, Pancreotonia 91.1%, Gastrotonia 0%, Pulmotonia 71.2%, Colonotonia 74.4%, Renotonia 37.5%, Vesicotonia 67.1% expect. 2. When we select AGCBR that is expert type III by reasoning system, diagnosis rate 77.51% of 8 constitution diagnosis expert system is expected, and the constitution diagnosis rate Hepatonia 93.4%, Cholecystonia 58.5%, Pancreotonia 91.1%, Gastrotonia 0%, Pulmotonia 73.1%, Colonotonia 64.4%, Renotonia 41.7%, Vesicotonia 72.2% expect. Conclusion : Based on this study, 8 constitution diagnosis expert system may give help to diagnose 8 constitution, and it is going to utilize as objective estimation tool of 8 constitution diagnosis, and further study for 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning) is needed to supplement this study.

• 대한한의진단학회지
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• 제12권1호
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• pp.142-184
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• 2008

Background: There was seldom study about method that diagnose 8 Constitution beside method of pulse diagnosis in 8 Constitution Medicine. Objectives: This study is to make out 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning). Methods: First, at case base construction process we constructed case base for CBR embodiment because gathering 925 cases all to patient who constitution is verified, and second, at study model establishment process superior expert system development by purpose CBR of reasoning process dividing fundamental type CBR that spend basis data value and expert type I II III CBR that reflect weight in basis data value according to advice expert opinion, and third, system embodiment process explained about way to give process and weight that diagnose constitution through Nearest Neighbor Method sampling process of CBR techniques, and fourth, at system estimation process we selected superior CBR model because comparing and estimate the diagnosis rate of expert system with fundamental type system (GECBR) model and expert type I II III CBR system (AVCBR, AACBR, AGCBR) model that reflect expert opinion in fundamental type system. GECBR and AGCBR chose on superior study model. Through such 4 study process, we developed 8 constitution diagnosis expert system lastly. Results: 1. When we select GECBR that is fundamental type by reasoning system, diagnosis rate 78.91% of 8 constitution diagnosis expert system is expected, and the constitution diagnosis rate Hepatonia 90.4%, Cholecystonia 63.0%, Pancreotonia 91.1%, Gastrotonia 0%, Pulmotonia 71.2%, Colonotonia 74.4%, Renotonia 37.5%, Vesicotonia 67.1% expect. 2. When we select AGCBR that is expert type III by reasoning system, diagnosis rate 77.51% of 8 constitution diagnosis expert system is expected, and the constitution diagnosis rate Hepatonia 93.4%, Cholecystonia 58.5%, Pancreotonia 91.1%, Gastrotonia 0%, Pulmotonia 73.1%, Colonotonia 64.4%, Renotonia 41.7%, Vesicotonia 72.2% expect. Conclusion: Based on this study, 8 constitution diagnosis expert system may give help to diagnose 8 constitution, and it is going to utilize as objective estimation tool of 8 constitution diagnosis, and further study for 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning) is needed to supplement this study.

• 품질경영학회지
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• 제32권2호
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• pp.168-190
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• 2004

In these days of world-wide business environment, the characteristics of quality management are variety, specialty, decentralization, totality, etc. Thus nowadays quality management is demanded to incorporate these new concepts. We propose a web-bused distributed expert system for this purpose. The system consists of four expert systems for design of experiment, acceptance inspection, statistical process control and reliability management corresponding to design quality, incoming-material quality, manufacturing quality and usability quality, respectively, throughout the total product life cycle. Each distributed expert system at the horizontal level in the hierarchy carries out its own quality jobs independently. At the lower level in the hierarchy there is an expert system for measurement analysis to provide reliable data, and at the upper level, an expert system for total quality management to coordinate, integrate and make final decisions. A prototype has been developed and its application is presented.

• 한국생산제조학회지
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• 제9권1호
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• pp.128-135
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• 2000

This paper presents a polishing expert system integrated with sensor information which can modify the polishing sequence and conditions initially determined by the system depending on the on-site polishing status. A practical system using AE sensor to detect the on-line polishing status is developed for the rotational polishing and the smoothly curved sur-face. Database and knowledge base for polishing processes are established by using the results of experiments and also expert's experience. Evaluations are performed for a die of headlight lamp by using both the sensor integrated expert sys-tem and the expert system without sensor. The test results show that the sensor integrated expert system provides more optimal polishing conditions since the proposed system takes advantage of on-line sensor information.

• 한국해양공학회지
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• 제11권1호
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• pp.36-43
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• 1997

Weld bead shape is an important measure for evaluation of weld quality. Many welding parameters have influence on the weld bead shape. The quantitative relationship between welding parameters and bead shape, however, is not determined yet because of their high complexity and many unknown factors. Fuzzy expert system is an advanced expert system which uses fuzzy rules and approximate reasoning. It is a vert useful tool for welding technology because is can process rationally the uncertain and inexact information such as the welding information. In this paper, the empirical and the qualitative relationship between welding parameters and bead shape are analyzed and represented by fuzzy rules. They are converted to the quantitative relationship by use of approximate reasoning of fuzzy expert system. Weld bead shape is estimated from the welding parameters using fuzzy expert system. The result of comparison between measured values of weld bead by welding experiments and the estimates values by fuzzy expert system shows a good consistancy.

• 대한전기학회논문지
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• 제41권8호
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• pp.831-840
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• 1992

This paper presents an efficient short-term generation scheduling method using a rule-based expert/consulting system approach to assist electric energy system operators and planners. The expert system approach is applied to improve the Dynamic Programming(DP) based generation scheduling algorithm. In the selection procedure of the feasible combinations of generating units at each stage, automatic consulting on the manipulation of several constraints such as the minimum up time, the minimum down time and the maximum running time constraints of generating units will be performed by the expert/consulting system. In order to maximize the solution feasibility, the aforementioned constraints are controlled by a rule-based expert system, that is, instead of imposing penalty cost to those constraint violated combinations, which sometimes may become the very reason of no existing solution, several constraints will be manipulated within their flexibilities using the rules and facts that are established by domain experts. In this paper, for the purpose of implementing the consulting of several constraints during the dynamic process of generation scheduling, an expert system named STGSCS is developed. As a building tool of the expert system, C Language Integrated Production System(CLIPS) is used. The effectiveness of the proposed algorithm has been demonstrated by applying it to a model electric energy system.

• 대한전기학회논문지
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• 제38권8호
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• pp.617-628
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• 1989

In systematic tuning of digital STC parameters, systems with time-varying parameters and systems with time-varying delays are studied individually because of many preconditions and difficulties. In order to eliminate all these difficulties effectively, the expert control technique is required to enhance STC control functions. In this paper, an expert controller, a STC utilizing expert control technique, for process control is designed. The expert controller is composed of an unstability indicator for detecting plant unstability, an expert back-up controller and an expert STC which are switched each other by the unstability indication, and expert system with knowledge base and inference engine. This expert controller is able to perform control functions successfuly for the following` 1) a system which has unknown and time-varying delay time, 2) a time-varying system which has unknown parameters, and 3) a system with minimun and non-minimum phase. The robust control function is demonstrated by computer simulations.

• 한국정보시스템학회지:정보시스템연구
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• 제1권
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• pp.149-178
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• 1992

The field of Artificial Intelligence (AI) is growing, and many firms are investing in expert system, one of AI's subfields. An expert system is defined as a computer program designed to replicate some aspect of the decision making of one or more experts and to be used by nonexperts. The kernel of an expert system is the knowledge base, which consists of the facts and rules that represent the expert's knowledge. Firms need expert systems for training employees to provide competitive advantage. This paper describes the model of an instructional expert training system which interfaces to external programs, such as an ASCII file, a work-sheet program, and a database program. A model for such an expert training system, and its prototype have been developed to demonstrate its functionality. A modular knowledge base has been developed and implemented in support of this study. The modularized knowledge base offers the user an easy and quick maintenance of facts and rules, which are frequently required to change in future.

• 품질경영학회지
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• 제20권1호
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• pp.147-157
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• 1992

This article describes a prototype expert system for yarn spinning process planning in textile industry. This expert system is intended as a consultant to give the technicians interactive assistance for the appropriate process planning in accordance with used materials, required count, and other factors affected yarn spinning by means of many types of machine. Also, this system has the other function that can be compared the standard values with the measured ones for quality characteristics control. VP-EXPERT-a rule-based microcomputer expert system development tool-provides the expert system components for this development. The details of knowledge organization, rule representation, inference reasoning process, and performance of this expert system are demonstrated with the practical yarn spinning operations.

• Journal of Biosystems Engineering
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• 제22권3호
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• pp.343-350
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• 1997

In farm management, many factors should be considered to select optimum farm machinery Some factors such as fm size can be quantified, but other factors such as working experience can not be. Futhermore, as several factors are missed and assumptions are made for the selection using conventional computer programs, the result is sometimes questionable. This problem can be solved using artificial intelligent techniques such as expert system. In this study, an expert system was developed to select optimum machinery by considering available working days, machinery to on, farming environments, labor cost, population, etc. It also took into account the characteristics of machinery, turning radius, easiness of operation, subsidy, loan to purchase, asset. farmers age, Rest Metabolic Rate, and working experience, etc. Expertise and experience of human experts were utilized to develop the expert system. The developed expert system was evaluated by the human experts and others, and it was proved to be practically useful fir farmers.