• 지능정보연구
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• 제6권1호
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• pp.97-112
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• 2000

The basic idea of case-based reasoning is to solve a new problem using the previous problem-solving experiences. In this research we develop a case-based reasoning system for equipment malfunction diagnosis. We first divide the case base into clusters using the case-based clustering technique. Then we develop an appropriate case-based diagnostic system for each cluster. In other words for individual cluster a different case-based diagnostic system which uses different weights for attributes is developed. As a result multiple case-based reasoning system are operating to solve a diagnostic problem. In comparison to the performance of the single case-based reasoning system our system reduces the computation time by 50% and increases the accuracy by 5% point.

• 산업경영시스템학회지
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• 제21권46호
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• pp.181-196
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• 1998

The aim of this research is the development of a CAPP system which can use the old experience of process planning to generate a process plan for a new part and learn from its own experience using the concept of stratified case-based reasoning(CBR). A process plan is determined through the hierarchical process planning procedure that is based on the hierarchical feature structure of a part. Each part and case have their own multiple abstractions that are determined by the feature structure of the part. Retrieving the case in stratified case-based process planning is accomplished by retrieving the abstraction that is most similar to the input part abstraction in each abstraction level of the case-base. A new process plan is made by the adaptation that translates the old case's process plan into the process plan of a new part. Operations, machines and tools, setups and operation sequence in each setup are determined in the adaptation of abstraction using some algorithms and the reasoning based on knowledge-base. By saving a new part and its process plan as a case, the system can use this new case in the future to generate a process plan of a similar part. That is, the system can learn its own experience of process planning. A new case is stored by adding the new abstractions that are required to save as the new abstraction to the existing abstractions in the case-base.

• 한국컴퓨터정보학회논문지
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• 제11권2호
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• pp.121-129
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• 2006

퍼지기법을 이용한 룰-기반(rule-based) 전문가 시스템에서는 사용자의 조건입력에 따라 여러 가지의 룰(rule)들을 추론하여, 가장 적절한 신호주기를 산출해낸다. 그러나 입력조건을 사용자의 판단에만 의존함으로 해서 객관성을 잃을 수 있는 단점이 있다. 본 논문에서는 케이스-기반시스템(case-based system)의 기법을 추가함으로써 그러한 객관성의 문제를 보완하고자 한다. 기존의 통계치로 각 요일별, 각 계절별, 여러 상황들에 대한 케이스(case)를 시스템에 저장함으로써 적절히 활용할 수 있도록 교통신호 제어 전문가 시스템의 모델을 제안한다.

• Journal of Ship and Ocean Technology
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• 제5권3호
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• pp.27-35
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• 2001

In this research, hybrid method with case-based reasoning and rule-based reasoning is applied. Using case-based reasoning, design experts'experience and know-how are effectively represented in order to obtain a proper configuration of midship section in the initial ship design stage. Since there is not sufficient domain knowledge available to us, traditional case-adaptation algorithms cannot be applied to our problem, i.e., creating the configuration of midship section. Thus, new case-adaptation algorithms not requiring any domain knowledge are developed antral applied to our problem. Using the knowledge representation of DnV rules, rule-based reasoning can perform deductive inference in order to obtain the scantling of midship section efficiently. The results from the case-based reasoning and the rule-based reasoning are examined by comparing the results with various conventional methods. And the reasonability of our results is verified by comparing the results wish actual values from parent ship.

• Asia pacific journal of information systems
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• 제25권4호
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• pp.626-641
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• 2015

Conventional case-based reasoning (CBR) does not perform efficiently for high-volume datasets because of case retrieval time. To overcome this problem, previous research suggested clustering a case base into several small groups and retrieving neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performance than the conventional CBR. This paper proposes a new case-based reasoning method called the clustering-merging CBR (CM-CBR). The CM-CBR method dynamically indexes a search pool to retrieve neighbors considering the distance between a target case and the centroid of a corresponding cluster. This method is applied to three real-life medical datasets. Results show that the proposed CM-CBR method produces similar or better predictive performance than the conventional CBR and clustering-CBR methods in numerous cases with significantly less computational cost.

• 한국전자거래학회지
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• 제9권3호
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• pp.129-144
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• 2004

컴포넌트 기반 개발에 사용되는 CASE 도구는 기본적으로 모델링 기능, 프로젝트 관리 기능, 그리고 구현 및 테스트 지원 기능 등이 필요하다. 본 논문에서는 컴포넌트 기반 개발 시에 사용되는 CASE 도구의 기능적 요구사항을 제시한다. 기 존재하는 컴포넌트 기반 개발 도구들로부터 도구의 기능적 요구사항을 도출하여 분석/설계, 프로젝트 관리, 구현 및 테스트, 기타 기능 지원 등으로 분류하여 제시하고, 개발관리 기능을 추가하여 컴포넌트 기반 개발을 위한 CASE 도구를 제안한다.

• 한국정보처리학회논문지
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• 제2권5호
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• pp.721-732
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• 1995

IPSE(Integrated Project Support Environment) 도구는 언어 중심적이고, 개발방 법론에 근거한 툴셋 형태로 제공되는 현재의 CASE 도구들의 주요 기능들을 하나로 통 합하고자 하는 노력의 결과로 볼 수 있다. 프로세스 모델을 기반으로 한 IPSE 접근방 법이 통합 CASE 구현을 위한 효과적인 방법으로 여겨진다. PM-CASE(Process Model based CASE)도구는 새로운 프로세스 모델링 기법에 의해 프로세스를 표현한 다이아그 램을 작성하기 위한 시제품으로서, 프로세스내의 태스크 관련 속성들을 정의 하고 데 이터 베이스에 저장한다. 이들 속성들은 태스크 수행 중에 만들어진 산출물에 대한 정 보의 검색 및 태스크와 연관된 도구를 호출하는데 사용된다. 본 논문에서는 PSEE (Process centered Software Engineering Environments) 도구들을 비교 분석하고, PM- CASE 도구의 기본개념, 구조, 설계에 대한 기술을 통해 효과적인 소프트웨어 개발관리 를 지원하는 프로세스 모델 기반 CASE 도구의 구축방법을 제시한다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2005년도 추계학술대회 및 정기총회
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• pp.237-240
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• 2005

This paper describer a design expert system which determines the design values of shadow mask using Case-Based Reasoning. In Case-Based Reasoning, it is important to both retrieve similar cases and adapt the cases to meet the design specifications exactly. Especially, the difficulty in automating the adaptation process will prevent the designers from using the design expert systems efficiently and easily. This paper explains knowledge-based design support systems for shadow mask through neural network-based case adaptation. Specifically, we developed 1) representing design knowledge and 2) adaptive case-based reasoning method using RBFN (Radial Basis Function Network).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.932-951
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• 2021

The effectiveness of testing in Model-based Testing (MBT) for Software Product Line (SPL) can be achieved by considering fault detection in test case. The lack of fault consideration caused test case in test suite to be listed randomly. Test Case Prioritization (TCP) is one of regression techniques that is adaptively capable to detect faults as early as possible by reordering test cases based on fault detection rate. However, there is a lack of studies that measured faults in MBT for SPL. This paper proposes a Test Case Prioritization (TCP) approach based on dissimilarity and string based distance called Last Minimal for Local Maximal Distance (LM-LMD) with Dice-Jaro-Winkler Dissimilarity. LM-LMD with Dice-Jaro-Winkler Dissimilarity adopts Local Maximum Distance as the prioritization algorithm and Dice-Jaro-Winkler similarity measure to evaluate distance among test cases. This work is based on the test case generated from statechart in Software Product Line (SPL) domain context. Our results are promising as LM-LMD with Dice-Jaro-Winkler Dissimilarity outperformed the original Local Maximum Distance, Global Maximum Distance and Enhanced All-yes Configuration algorithm in terms of Average Fault Detection Rate (APFD) and average prioritization time.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.883-889
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• 2009

The importance of cost estimate in early stage such has been increasing due to market change and severe competition in construction industry. Because the adjustable budget is only 20% after design stage, most of the crucial decisions to influence cost is made in the early stage. However, in the early stage, the project scope is not defined completely so that estimator has inaccurate information to make critical decision. Therefore, this research suggests the cost estimate method using case-based reasoning. Case-based reasoning is appropriate for the early cost estimating, as it has the strength of rapidity and convenience in cost estimation. This research analyzes 84 actual data of public apartment on the scale of 11~15 stories. In order to extract the most similar case, at the first step this research identifies influence factors and calculates attribute similarity. In case-based reasoning, the most challenging task is determining attribute weight. At the third step, this research calculates case similarity which is aggregated attribute similarity multipled by attribute weight. Finally, extracts the most similar case which has the highest score of case similarity.