• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1996년도 하계학술대회 논문집 B
• /
• pp.734-736
• /
• 1996

This paper presents a method of calculating a selective number of eigenvalues in power systems, which are rightmost, or are largest modulus. The modified Arnoldi method in conjunction with implicit shift OR-algorithm is used to calculate the rightmost eigenvalues. Algorithm requires neither a prior knowledge of the specified shifts nor the calculation of inverse matrix. The key advantage of the algorithm is its ability to converge to the wanted eigenvalues at once. The method is compared with the modified Arnoldi method combined with S-matrix transformation, where the eigenvalues having the largest modulus are to be determined. The two methods are applied to the reduced Kansai system. Convergence characteristics and performances are compared. Results show that both methods are robust and has good convergence properties. However, the implicit shift OR method is seen to be faster than the S-matrix method under the same condition.

• 한국산학기술학회논문지
• /
• 제13권1호
• /
• pp.355-363
• /
• 2012

다중 에이전트 구조와 블랙보드 구조를 통합하면 두 구조의 특징들과 장점들을 필요로 하는 응용 분야에 대응할 수 있는 가능성이 생긴다. 본 논문은 Rete 네트워크에 기반을 둔 블랙보드 이벤트 탐지 메커니즘과 블랙보드 이벤트 기반의 암시적 호출 구조 패턴을 함께 사용하여 다중 에이전트 구조에 블랙보드 구조를 통합하는 방안을 제안한다. 다중 에이전트 구조에 블랙보드 구조를 통합하기 위하여 이벤트 기반의 암시적 호출 구조 패턴을 사용하는 것은 구성 요소들 간의 결합도(coupling)의 감소와 지식 원천 에이전트들의 제어의 융통성의 증대 등의 면에서 바람직하다. 하지만 이벤트 기반의 암시적 호출 구조 패턴 자체는 그것을 사용하는 구조의 성능을 고려하고 있지 않다. 본 논문이 제안하는 통합 구조의 성능을 향상시키려면 지식 원천 에이전트들을 활성화시킬 수 있는 블랙보드 이벤트들의 발생을 신속하게 탐지할 수 있어야 한다. 본 논문이 제안하는 통합 방안은 Rete 네트워크 기반의 블랙보드 이벤트 탐지 메커니즘을 사용하여 블랙보드 이벤트 기반의 암시적 호출 구조 패턴을 이용한 통합 구조에서 지식 원천 에이전트들을 활성화시킬 수 있는 블랙보드 이벤트들이 효율적으로 탐지될 수 있도록 한다.

• 한국어교육
• /
• 제29권4호
• /
• pp.93-112
• /
• 2018

The purpose of this study is to deal with vocabulary in KFL. As a result of this study, learners learned vocabulary on average 43 points through contextual inference and introduction of the class to activate background knowledge. In particular, the implicit method showed the highest learning rate of 52 points, and the thematic method had a 41 point-learning rate. In contrast, the semantic method was the lowest with a 25 point-learning rate. There was no significant difference in the improvement rate of upper vocabulary learners, but in the case of the lower learner, there was significant difference in the improvement rate. The difference was not significant in the post-test relative gain rate of upper learners, but there was significant in lower learners. In the delayed test relative gain rate, the difference was significant in all groups. There was correlation between vocabulary difficulty and score, but there was no correlation with the thematic method. And there was no correlation between vocabulary difficulty, improvement rate and relative gain rate in all three classes. However, content understanding, lexical grade, improvement rate, and relative gain rate showed a significant correlation.

• 한국시뮬레이션학회:학술대회논문집
• /
• 한국시뮬레이션학회 1994년도 추계학술발표회 및 정기총회
• /
• pp.12-12
• /
• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
• /
• 제8권2호
• /
• pp.29-34
• /
• 2019

우선순위 큐은 근본적인 자료 구조 중의 하나이며 오랫동안 많은 연구가 이루어여 왔다. 본 논문에서는 IMI-힙이라고 하는 묵시 양단 우선순위 큐를 제안한다. 제안된 IMI-힙에서는 삽입에 O(1) 전이시간이 걸리고 최소값과 최대값 삭제 연산에 각각 O(logn) 시간이 걸린다. 기존에 발표된 묵시 양단 우선순위 큐는 삽입과 최소/최대값 삭제에 모두 O(logn) 시간이 걸리는 것으로 본 저자는 알고 있다. 따라서 제안된 IMI-힙은 삽입 시간 복잡도에 있어서 기존의 힙보다 우수하다.

• 한국산업정보학회논문지
• /
• 제13권5호
• /
• pp.55-65
• /
• 2008

기업의 전략적 의사결정자는 불확실성과 복잡성에 직면해왔다. 그리고 그들은 이러한 환경 하에서 의사결정을 내려야 함에도 불구하고 그들의 의사결정에 필요한 충분한 시간, 인력, 예산, 그리고 지식이 충분히 주어지지 않는다. 그래서 그들은 그 분야에 대한 암묵적 지식을 지닌 전문가들의 지원을 받는 수 밖에 없다. 그러나 의사결정자들이 어떤 문제에 직면할 때 마다 의사결정에 필요한 새로운 지식을 창조하고 변형하고 결합하고 응용하는 다른 절차나 방법을 발견하는 것은 매우 어렵다. 본 논문은 노나카에 의해 제안된 지식변환과정을 이용함으로써 전략적 의사결정을 지원할 새로운 방법을 제안한다. 본 연구는 컨설팅 산업분야에서 전략적 의사결정의 응용사례를 예시한다. 이 논문은 제안된 방법에 기초한 의사결정지원기법으로서 인지지도를 사용한다.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
• /
• pp.393-399
• /
• 2001

The Purpose of this paper is how KM is implemented and executed to reform the organization in the change management aspect and how its current KM can be developed in the future, mainly based on the organizational system, business process, and information system related to KM. This Paper is longitudinal case study of Knowledge Management at LG-EDS Systems. The effective approach to undertake KM is phase. First, it is structured to share explicit knowledge for better performance and then implicit knowledge for best performance. But, This method had some limitations. So, LG-EDS systems integrated KMS-Knowledge Portal-to facilitate cooperation and improve contents quality.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 2005년도 추계학술대회 논문집
• /
• pp.798-803
• /
• 2005

The increasing complexity of modem products requires the effective management of design knowledge, which partly resides in the product itself on the one hand. On the other hand, a lot of knowledge is gathered and/or generated during the design process, but disappears as the design project concludes. This paper describes a knowledge representation method to accommodate the implicit design knowledge. The method is based on the FBS(Function-Behavior-Structure) model and extends the object ontology with constraint entity. An example to represent the injection mold design knowledge is given to show its applicability.

• 지식경영연구
• /
• 제2권1호
• /
• pp.25-44
• /
• 2001

There are two types of organizational knowledge in terms of its creation process: experiential and analytical knowledge. The experiential knowledge is created by repetitive experiences of an individual or team through task execution, while the analytical knowledge is acquired by analyzing accumulated data or information in the organization. The experiential knowledge often remains tacit or implicit in the organization because it is primarily acquired at an individual or team level. Therefore, the issue on the experiential knowledge is to share it actively within the organization. On the other hand, the analytical knowledge is explicit in its nature since it is extracted from data or information. Thus, it is important to guide a systematic creation of the analytical knowledge rather than encourage to share it. The current trend of "knowledge management" mainly focuses on the experiential knowledge - know-how, idea, case, etc - and neglects another important knowledge in the organization. i. e., analytical knowledge. This paper tries to shed a new light on the "knowledge management" arena by introducing rather new perspective in the concept of knowledge. The purpose of this study is to identify the factors affecting the analytical knowledge creation in the organization. We conducted an exploratory case study of three companies with a previously defined research framework and found some critical factors for the analytical knowledge creation. They are "organizational resource", "effectiveness of feedback process", "data source management", and "experimental mind set". Finally, we proposed research model and propositions regarding the analytical knowledge creation in the organization.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
• /
• pp.278-282
• /
• 2001

The discovery of tacit knowledge from domain experts is one of the most exciting challenges in today\`s knowledge management. The nature of decision knowledge in determining the quality a firm\`s short-term liquidity is full of abstraction, ambiguity, and incompleteness, and presents a typical tacit knowledge extraction problem. In dealing with knowledge discovery of this nature, we propose a scheme that integrates both knowledge elicitation and knowledge discovery in the knowledge engineering processes. The knowledge elicitation component applies the Verbal Protocol Analysis to establish industrial cases as the basic knowledge data set. The knowledge discovery component then applies fuzzy clustering to the data set to build a fuzzy knowledge based system, which consists of a set of fuzzy rules representing the decision knowledge, and membership functions of each decision factor for verifying linguistic expression in the rules. The experimental results confirm that the proposed scheme can effectively discover the expert\`s tacit knowledge, and works as a feedback mechanism for human experts to fine-tune the conversion processes of converting tacit knowledge into implicit knowledge.