• Nuclear Engineering and Technology
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• 제46권6호
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• pp.753-772
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• 2014

The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM), which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2003년도 춘계학술대회
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• pp.400-409
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• 2003

Collaborative filtering (CF) recommendation is a knowledge sharing technology for distribution of opinions and facilitating contacts in network society between people with similar interests. The main concerns of the CF algorithm are about prediction accuracy, speed of response time, problem of data sparsity, and scalability. In general, the efforts of improving prediction algorithms and lessening response time are decoupled. We propose a three-step CF recommendation model which is composed of profiling, inferring, and predicting steps while considering prediction accuracy and computing speed simultaneously. This model combines a CF algorithm with two machine learning processes, SOM (Self-Organizing Map) and CBR (Case Based Reasoning) by changing an unsupervised clustering problem into a supervised user preference reasoning problem, which is a novel approach for the CF recommendation field. This paper demonstrates the utility of the CF recommendation based on SOM cluster-indexing CBR with validation against control algorithms through an open dataset of user preference.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.182-186
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• 2011

Early cost estimates are important to decision-making for a construction project. Moreover, the possibility of reducing the project cost is getting less as the project is progressed. Case-based reasoning (CBR), which can be viewed as an effective method for early cost estimating, is widely utilized recently. Early cost estimates using CBR have advantages over the traditional ones as they produce reasonable outputs and self-studying is possible by simply adding new cases. Case-based reasoning is composed of a cycle of retrieve, reuse, revise, and retain process. However, in the majority of research cases, they are focused on how to retrieve the similar cases, instead of revising the cases which is expected to increase accuracy results of cost estimation. This research suggests a method of revising retrieved similar cases in a GA-CBR cost model which is widely studied and utilized for early cost estimating recently. To validate the proposed method, case study is conducted based on Korean public apartment projects.

• 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.

• Asia pacific journal of information systems
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• 제16권4호
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• pp.217-238
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• 2006

In this study, we propose a virtual community recommendation model based on user behavioral models. It is designed to recommend optimal virtual communities for an active user by applying case-based reasoning (CBR) using behavioral factors suggested in the technology acceptance model (TAM) and its extensions. Also, it is designed to filter its case-base by considering the user's needs type before applying CBR. To test the usefulness of our model, we conduct two-step validation - experimental validation for the collected data, and survey validation for investigating the actual satisfaction level. Experimental results show that our model presents effective recommendation results in an efficient way. In addition, they also show that the information on the user's needs type may generate opportunities for cross-selling other commercial items.

• 한국가정과교육학회지
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• 제21권2호
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• pp.187-202
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• 2009

본 연구는 고등학교 1학년 기술 가정 교과의 '결혼과 육아' 단원에서 '부모됨'에 대한 수업 내용을 중심으로 11종 교과서와 관련 자료를 분석하여 추출한 수업 목표를 가지고 실천적 추론 수업 과정으로 재구성하여 교수 학습 과정안을 개발하고 실제교실 수업에 적용하여 실천적 추론 수업 방식의 효과를 평가하는데 목적을 두었다. 개발된 6차시 교수 학습 과정안은 실천적 문제 '부모가 된다는 것이 나에게 의미하는 것이 무엇인가?'로 1, 2차시를, '좋은 부모가 되기 위해 나는 무엇을 준비해야 하는가?'로 3, 4, 5차시를, '바람직한 부모역할을 위해 나는 무엇을 해야 하는가?'로 6차시 교수 학습 과정안을 학교 수업에 적용하였다. 적용 대상은 경기도 이천시 소재의 고등학교 1학년 남녀 합반의 5개 학급, 총 180명을 대상으로 하였다. 부모됨 단원의 하위 요소인 부모됨의 의미와 동기, 부모됨의 준비, 부모됨의 역할로 나누어 대응표본 t-검정을 통해 학습자의 부모됨에 대한 인식의 향상을 가져오는지 그 효과에 대해 결과를 분석하였다. 부모됨 단원을 실천적 추론 수업 방식으로 적용하였을 경우 학습자들의 인식 변화에 긍정적인 결과를 보였다. 또한 실천적 추론 수업 방식은 학습자들의 흥미와 참여, 이해를 높이는 결과를 가져왔다. 본 연구는 가정과교육에 적합한 교수 학습 방법인 실천적 추론 수업을 다양한 학습내용과 학습활동으로 학생들의 흥미와 수업 참여도를 증대시켜 효과적인 수업이 가능하다는 점에서 교육적 의의를 가진다고 할 수 있다.

• 전자공학회논문지C
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• 제34C권5호
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• pp.93-102
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• 1997

Conventional expert systems have difficulties in the inference on time-varing situations because they don't have the structure for processing time related informations and rule representation method to describe time explicitely. Some expert systems capable of temporal reasoning are not applicable to the domain in which state changes happen by unpredictble events that cannot be represented by periodic changes of data. In this paper, an event based temporal reasoning method is proposed. It is capable of processing te unpredictable events, representing the knowledge related to event and time, and infering by that knowledge as well as infering by periodically time-varing data. The NEO/temporal, an temporal inference engine, is implemented by applying the proposed temporal reasoning situation assessment and decision supporting system is implemented to show the benefits of the proposed temporal information processing model.

• 품질경영학회지
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• 제24권3호
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• pp.133-144
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• 1996

In order to evaluate the effectiveness of fuzzy reasoning to sensory tests, in this paper, a non-linear fuzzy system model that can estimate the general evaluator obtained from a numerical example of test of taste is constructed. And the applicability of fuzzy reasoning to sensory test is discussed on the basis of errors occurred from the estimates in combination of attributes of objects and from the results of multi-regression analysis. This paper proved that fuzzy reasoning using fuzzy If-then rules is applicable to sensory test.

• 인지과학
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• 제15권4호
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• pp.15-20
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• 2004

유연성과 광범위성을 갖는 대규모 인지 시스템의 구축을 위해서는 전문적인 지식 뿐 아니라 상식 수준의 지식을 포함한 대용량 지시베이스의 구축이 필수 불가결하다. 이를 위해서는 효율적인 지식 표현 및 추론 기법이 핵심적 열할을 하게 될 것이다. 본 논문에서는 정성적 지식 표현 및 추론 기법을 이미 구축된 범용의 대용량 Cyc 지식베이스와 접목하여, 일상의 상식적인 추론을 제공할 수 있는 인지 시스템을 소개한다. 본 시스템은 구현되어 여러 예제에 적용되어 그 실효성을 입증한 수 있었다.