• 한국전자거래학회지
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• 제8권1호
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• pp.55-70
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• 2003

With the gradual growth of the electronic commerce various forms of shopping malls are constructed, and their searching methods and function are studied many ways. However, the recent outcome is still inadequate to search for goods for the tastes and demands of customers. To construct the shopping mall on the electronic commerce and help customers with purchasing goods, the efficient interface for the customers to contact the shopping malls should be founded and the customers should be able to search the goods they want. Therefore, in this paper, we designed the Intelligent Integration Agent System (IIAS) using the multi-agent formed by the integration agent which integrates the case based reasoning(CBR) and the rule based reasoning(RBR) and the user agent which manages users' profiles. IIAS performs the rule based reasoning on the subject issue first, then provides the unsatisfying search results from the rule-base reasoning to the customers through the user agent, which enables the search of the goods most similar to the ones that meet the tastes and demands of the customers. That is, the accuracy and the speed has been improved by reasoning with the similarity adjustable integration agent which can pick out the goods of customers wants by modifying the weights of properties according to those of the customers.

• Nuclear Engineering and Technology
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• 제22권2호
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• pp.128-138
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• 1990

본 논문에서는 원자로냉각재펌프 고장진단 전문가시스템 (ESRCP)에 대해 기술하였다. 이 시스템의 목적은 RCP의 고장진단과 함께 발전소 운전원에게 적절한 운전 조작 및 비상조치 사항 등을 알려주는데 있다. 진단을 위한 일차적 증상은 RCP 영역에 관련된 경보들이다. 경보처리는 Rule-based Deduction 또는 Priority Factor Operation에 의한다. 고장진단은 Rule-based Deduction이나 Bayesian Inference에 의해 수행된다. 각종 Sensor들의 측정값들은 정확한 원인을 진단하기 위해 필요로 하다 증상들이 부족하거나 불착실성을 나타낼 때는 Bayesian Inference로 고장을 진단한다.

• Communications for Statistical Applications and Methods
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• 제17권4호
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• pp.527-540
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• 2010

규칙기반 분류분석(rule-based classification analysis)은 직관적인 이해가 쉽고 알고리즘이 복잡하지 않아 최근 대용량 데이터마이닝에 많이 이용되는 기법이다. 하지만 현재의 규칙기반 분석은 여러 개의 규칙들을 찾은후 이 규칙들을 단순히 다수결이나 또는 중요도의 가중 합으로서 새로운 데이터를 분류한다. 본 연구에서는 다항분포를 이용한 이항데이터의 분류분석 기법을 규칙 조합방법에 응용하고자한다. 다향분포의 추정을 위해서는 변형된 반복 비율 적합(iterative proportional fitting; IPF) 알고리즘을 이용하여 최대 엔트로피 분포(entropy distribution)를 찾는다. 시뮬레이션 실험 결과 이 방법은 두 집단의 데이터가 서로 유사한 경우 어느 정도 의미 있는 분류 결과를 보여주였다.

• 한국환경과학회지
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• 제15권3호
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• pp.261-269
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• 2006

In this study, an optimization technique was developed from the application of allocation rule. The results obtained from the water supply analysis and reliability indices analysis of Andong dam and Imha dam which are consist of parallel reservoir system are summarized as the followings; Allocation rule(C) is effective technique at the parallel reservoir system because results of the water supply analysis, storage analysis and reliability indices analysis is calculated reasonable results. Also, reliability indices analysis results are not sufficient occurrence based reliability or quantity based reliability. Thus reliability indices analysis are need as occurrence based reliability, quantity based reliability vulnerability, resilience, average water supply deficits and average storage. And water supply condition is better varying water supply condition than constant water supply condition.

• 지능정보연구
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• 제7권1호
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• pp.161-175
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• 2001

이 논문에서는 규칙 기반 추론 시스템에서 추론이 수행되는 과정에서 처리 대상인 입력 정보들에 모순이 존재하는 경우에 모순된 정보를 검출하기 위한 기법을 제안한다. 이 논문에서 제안한 기법은 ATMS의 라벨 표현 방법과 관리 기법을 개선하여 불확실성 값을 갖는 입력 정보를 처리할 수 있도록 하고, 상반된 입력 정보들로 인하여 배타적인 결론들을 동시에 지지하는 경우에 각 결론들과 지지하는 입력 정보들간의 모순을 검출할 수 있는 기법이 다.

• Transactions on Control, Automation and Systems Engineering
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• 제3권3호
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• pp.170-175
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• 2001

Q-learning is a kind of reinforcement learning where the agent solves the given task based on rewards received from the environment. Most research done in the field of Q-learning has focused on discrete domains, although the environment with which the agent must interact is generally continuous. Thus we need to devise some methods that enable Q-learning to be applicable to the continuous problem domain. In this paper, an extended fuzzy rule is proposed so that it can incorporate Q-learning. The interpolation technique, which is widely used in memory-based learning, is adopted to represent the appropriate Q value for current state and action pair in each extended fuzzy rule. The resulting structure based on the fuzzy inference system has the capability of solving the continuous state about the environment. The effectiveness of the proposed structure is shown through simulation on the cart-pole system.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2002년도 춘계학술대회논문집
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• pp.261-266
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• 2002

In this Paper, we Propose model-based tuning rules of the PID controller incorporating with genetic algorithms. Three sets of optimal PID parameters for step set-point tracking are obtained based on the first-order time delay model of plants and a genetic algorithm which minimizes performance indices(IAE, ISE and ITAE). Then tuning rules are obtained using the tuned parameter sets, potential rule models and a genetic algorithm. Simulation is carried out to verify the effectiveness of the proposed rules.

• 공학논문집
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• 제3권1호
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• pp.123-129
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• 1998

본 논문에서는 지능형 실시간 제어 시스템 구축을 위하여 근사값 계산 방법의 적용을 rule-based 시스템과 관련하여 도모한다. 자원 정보에 대한 획득 및 표현 방안을 탐색하고, 이를 구현하기 위한 소프트웨어 설계 및 구현된 시스템의 타당성을 판단하기 위한 기준을 제시한다.

• 산업경영시스템학회지
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• 제39권3호
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• pp.170-179
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• 2016

In this paper we have tackled the outstanding inventory planning problems over new product launching period in a more holistic manner by addressing first the definition of efficient business rules to effectively control and reduce the inventory risks followed by the rigorous explanations on the implementation guide on suggested inventory planning rules. It is not unusual for many companies in the consumer electronics market to make a great effort to reduce the time to launch a new product because the ability to bring out higher performing products in such a short time period greatly increases the probability for them to remain competitive in the high tech market. Among so many newly developed products, those products with new features and technologies appeal to many potential customers while products which fail to win customers by design and prices rapidly disappear in the market. To adapt to this business environment, those companies have been trying to find the answer to minimize the inventory of old products so they can move to next generation products quickly with less obsolete material. In the experimental implementation of our rule-based inventory planning, Company 'S' reduced the inventory cost for the outgoing products as low as 49% of its peak level of its preceding product version in just 5 month after the adoption of rule-based inventory planning process and system. This paper concluded the subject with a suggestion that the best performance of rule-based inventory planning is guaranteed not from one-time campaign of process improvement along with system development but the decision maker's continuing support and attention even without seeing any upcoming business crisis.

• 한국통신학회논문지
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• 제41권11호
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• pp.1456-1462
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• 2016

본 논문에서는 규칙 기반의 4성부 합창 음악 생성 과정에 화성 진행 학습 모델을 적용해 보고자 한다. 제안하는 시스템은 32음의 멜로디를 입력으로 받아 다른 세 성부를 화성학의 규칙에 맞게 완성시켜 주며, 그 과정에서 사용하는 화성 진행을 CRBM 모델을 이용하여 예측한다. 학습 데이터는 화성학 교육 자료집에서 다수 발췌하였으며, 화성 진행을 조성에 독립적으로 추출하여 주어진 데이터를 효과적으로 활용할 수 있도록 하였다. 학습 모델을 적용한 결과물이 기존의 규칙 기반 4성부 합창 음악에 비해 보다 자연스러운 진행을 보임이 확인되었다.