• 한국정보시스템학회지:정보시스템연구
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• 제18권3호
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• pp.231-249
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• 2009

Recently, plant construction industries are enjoying a favorable business climate centering around developing countries and oil producing countries rich in oil money. This paper proposes a methodology of implementing case-based reasoning(CBR) system for managing knowledge like lessons learned and various documents accumulated in performing power plant construction projects which are receiving a lot of order from foreign countries such as the Middle East, etc. Our methodology is consisted of 10 steps : user requirement gathering, information modeling, case modeling, case base design, similarity function design, user interface design, case base building, CBR module development, user interface implementation, integration test. Also, to illustrate the effectiveness of proposed methodology, the real CBR system is implemented for the plant business division of 'H' company which has international competitiveness in the field of plant construction industry. At present, the implemented CBR system is successfully utilizing as storing, sharing, and reusing knowledge which is accumulated in performing power plant construction projects in the target enterprise.

• 산업경영시스템학회지
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• 제22권51호
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• pp.129-138
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• 1999

The aim of this research is the development of an automated fixture planning system for prismatic parts using the case-based reasoning (CBR). CBR is the problem solving paradigm that uses the similarity between a new problem and old cases to solve the new problem. This research uses CBR for the fixture planning. A case is composed with the information of the part, the components of fixture and the method of fixing for the part. The basic procedure is the retrieval and adaptation for the case, and this research presents the method of retrieval that selects most similar case to the new situation. The retrieval-step is divided into an index matching and an aggregated matching. The adaptation is accomplished by the modification, which transforms the selected case to the solution of the situation of the input part by the specified CBR algorithm. The components of fixture and the method of fixing are determined for a new part by the procedure.

• 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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1997년도 추계학술대회발표논문집; 홍익대학교, 서울; 1 Nov. 1997
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• pp.181-184
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• 1997

Practical applications of learning systems usually involve complex domains exhibiting nonlinear behavior and dilution by noise. Consequently, an intelligent system must be able to adapt to nonlinear processes as well as probabilistic phenomena. An important class of application for a knowledge based systems in prediction: forecasting the future trajectory of a process as well as the consequences of any decision made by e system. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes in the form of chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a Henon process in the presence of various patterns of noise.

• 한국건축시공학회지
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• 제12권5호
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• pp.518-527
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• 2012

This study uses a hybrid estimation tool for effective cost data management of building projects, and develops a realistic cost estimation model. The method makes use of newly available information as the project progresses, and project cost and percentage progress are analyzed and used as inputs for the developed system. For model development, case-based reasoning (CBR) is proposed, as it enables complex nonlinear mapping. This study also investigates analytic hierarchy process (AHP) for weight generation and applies them to a real project case. Real case studies are used to demonstrate and validate the benefits of the proposed approach. By using this method, an evaluation of actual project performance can be developed that appropriately considers the natural variability of construction costs.

• 한국강구조학회 논문집
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• 제23권5호
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• pp.557-568
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• 2011

공공 건설공사에서 공사 단계별 합리적인 공사비를 산정하는 것은 국가 예산의 효율적 확보 및 집행 등에 있어 매우 중요한 요소이다. 본 논문에서는 사업 초기단계의 가용정보가 제한된 조건에서 사례기반을 적용하여 강박스거더교의 개략공사비 추정 방안을 제시하였다. 또한 공사비 예측모델을 기존 설계사례에 대해 적용하여 본 논문에서 제시한 개략공사비 추정 모델의 정확성을 검증하였다. 연구 결과, 오차율은 비교적 안정적인 결과를 도출할 수 있었다. 따라서 국가 예산의 집행이나 수립에서 개략공사비 추정을 효율적으로 제시 할 수 있을 것으로 판단된다.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2008년도 정기학술발표대회 논문집
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• pp.445-448
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• 2008

국내 도로건설사업에 있어서 개략공사비 산정 기준은 건설교통부 및 기획예산처, 한국도로공사 등에서 제시하는 평균 건설단가를 기준으로 활용하고 있다. 이때 도로의 등급, 구조물 추간의 구성 비율 등에 따라 공사비를 도정하고 있으나 다양한 공사 특성을 반영하고, 지속적인 공사비 갱신의 기준 등에 한계를 가지고 있다. 대규모 재원이 투입되는 건설공사의 공사비를 합리적인 방법으로 적정하게 예측하는 것은 사업비 관리 측면에서 필수적인 요소는 기술이라 할 수 있다. 본 연구에서는 기획단계에서 가용한 정보를 활용하여 공사비를 예측할 수 있는 사에 기반추론 PSC BEAM교의 개략공사비 산정모델을 개발하였다. 제시된 공사비 예측모델을 검증하기 위하여 표본교량을 대상으로 공사비를 추정한 결과 $-11.92%{\sim}3.20%$의 추정편차를 나타내었으며, 기존 개략공사비 산정 기준에 비해 신뢰도가 향상되었다.

• 정보보호학회논문지
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• 제18권4호
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• pp.135-141
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• 2008

사이버 침해사고와 해킹의 위험성이 증대되고 있다. 이를 해결하기 위하여 정보보호기술중에서 보안위험분석 분야의 연구가 활발하게 이루어지고 있다. 하지만 평가를 위해서는 적지 않은 평가비용, 수개월의 평가기간, 평가 참여인원, 평가후의 보안대책비용, 보안관리비용에 대한 부담이 클 수밖에 없다. 이에 따라, 본 논문에서는 정량평가 형태의 위험분석평가를 프로젝트단위로 관리하며, 평가기간 및 적정 평가자 선정을 위한 사례기반추론알고리즘을 이용한 위험분석방법론 제안한다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2002년도 추계정기학술대회
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• pp.491-501
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• 2002

Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.