• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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• pp.277-280
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• 2006

Most real world design evaluation and risk-based decision support combine quantitative and qualitative (linguistic) variables. Decision-making based on conventional mathematics that combines qualitative and quantitative concepts always exhibit difficulty in modelling actual problems. The successful selection process for choosing a design/procurement proposal is based on a high degree of technical integrity, safety levels and low costs in construction, corrective measures, maintenance, operation, inspection and preventive measures. However, the objectives of maximising the degree of technical performance, maximising the safety levels and minimising the costs incurred are usually in conflict, and the evaluation of the technical performance, safety and costs is always associated with uncertainties, especially for a novel system at the initial concept design stage. In this paper, a design-decision support framework using a composite structure methodology grounded in approximate reasoning approach and evidential reasoning method is suggested for design evaluation of machinery space of a ship engine room at the initial stages. It is a Multiple Attribute Decision-Making (MADM) or Multiple Criteria Decision Making (MCDM) framework, which provides a juxtaposition of cost, safety and technical performance of a system during evaluation to assist decision makers in selecting the winning design/procurement proposal that best satisfies the requirement in hand. An illustrative example is used to demonstrate the application of the proposed framework.

• 한국멀티미디어학회논문지
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• 제9권9호
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• pp.1095-1106
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• 2006

전자상거래시스템의 효율적인 운영과 관리를 위해서 더욱 많은 노력이 요구되고 있으며 고객의 요구에 대해서 가장 적절한 상품 정보를 제공함으로서 만족을 극대화할 수 있어야 한다. 이를 위해서 많은 지능형 에이전트기술을 사용한 전자상거래시스템이 도입되고 있다. 본 논문에서는 전자상거래시스템에서 개인 상품 추천 지원을 위한 사례기반추론기법과 다중크로스 셀링기법(Multi-Crossselling)을 기반으로 한 상품 추천시스템을 제안하였다. 제안한 시스템은 다중크로스셀링 기법을 통해 고객패턴의 유사값에 가까운 여러 상품을 추출하고 사례기반추론기법을 통해 특정 조건에서 고객의 요구에 대해 적절한 상품 정보를 제공하고자 한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.532-538
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• 1998

In this paper, a new adaptive fuzzy inference method using neural network based fuzzy reasoning is proposed to make a fuzzy logic control system more adaptive and more effective. In most cases, the design of a fuzzy inference system rely on the method in which an expert or a skilled human operator would operate in that special domain. However, if he has not expert knowledge for any nonlinear environment, it is difficult to control in order to optimize. Thus, using the proposed adaptive structure for the fuzzy reasoning system can controled more adaptive and more effective in nonlinear environment for changing input membership functions and output membership functions. The proposed fuzzy inference algorithm is called adaptive neuro-fuzzy control(ANFC). ANFC can adapt a proper membership function for nonlinear plant, based upon a minimum number of rules and an initial approximate membership function. Nonlinear function approximation and rotary inverted pendulum control system ar employed to demonstrate the viability of the proposed ANFC.

• 한국지능시스템학회논문지
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• 제3권2호
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• pp.3-17
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• 1993

The fuzzy pattern matching technique has been developed in the framework of fuzzy set and possibility theory in order to take into account the imprecision and the uncertainty pervading values which have to be compared to requirements (which may be fuzzy) in a pattern matching process. This paper restates the basic principles and extends them to situations where (sub)patterns are only required to be satisfied up to a given tolerance (which may be fuzzy), or where the different subparts of a compound pattern may have various levels of importance. Both cases correspond to a weakening of elementary patterns. which can be expressed by a fuzzy relations modelling an approximate equality or an uncertain strict equality respectively. We also study the more sophisticated case where some elementary patterns have not to be satisfied with the highest priority provided that weaker requirements remain satisfied. The fuzzy pattern matching technique applies in a variety of problems including the evaluation of soft queries with respect to a fuzzy database, the evaluation of the fuzzy condition parts of rules in approximate reasoning, or the evaluation of the belonging of an ill-known object to a flexible class in classification problems.

• 한국건설관리학회논문집
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• 제14권3호
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• pp.42-52
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• 2013

본 연구는 기존의 선형적인 공사비 예측방법의 한계를 극복하고 사례기반추론 (Case Based Reasoning, CBR)기법을 통해 기획단계의 실적정보를 활용하여 신뢰도 높은 공사비 예측 모델을 제시하는 것이 목적이다. 이를 위하여 사례기반추론 기법과 유전자알고리즘 (Genetic Algorithm, GA)의 선택연산을 복합적으로 활용한 스프레드시트 기반의 교량공사비 추론모델을 제시하였다. 추론모델의 검증을 위하여 국내 교량공사 시공사례 4건을 적용하였으며, 적용 결과 평균 8.69%의 오차율로 나타나 교량공사비의 예측 정확도가 타 분석방법과 비교하여 상대적으로 높은 것으로 파악하였다. 연구에서 제시된 교량공사비 예측모델은 초기 설계단계에서 상세제원에 대한 정보를 획득할 수 없을 경우에, 교량의 대표적 제원정보 만으로 공사비 선택범위를 최소화된 오차율로 예측할 수 있으므로, 개선된 보정 방법으로서 교량공사의 합리적인 개략공사비 산정에 활용될 수 있을 것으로 판단된다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
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• pp.237-240
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• 2001

An image processing and decision making method for the Automatic Surveillance System is proposed. The aim of our Automatic Surveillance System is to detect a moving object and make a decision on whether it is human or not. Various object features such as the ratio of the width and the length of the moving object, the distance dispersion between the principal axis and the object contour, the eigenvectors, the symmetric axes, and the areas if the segmented region are used in this paper. These features are not the unique and decisive characteristics for representing human Also, due to the outdoor image property, the object feature information is unavoidably vague and inaccurate. In order to make an efficient decision from the information, we use a fuzzy rules base system ai an approximate reasoning method. The fuzzy rules, combining various object features, are able to describe the conditions for making an intelligent decision. The fuzzy rule base system is initially constructed by heuristic approach and then, trained and tasted with input/output data Experimental result are shown, demonstrating the validity of our system.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.486-495
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• 2001

This paper describes an implementation of the interval based expert system for syndrome differential diagnosis of Oriental Traditional Medicine (OTM). An approximate reasoning model using fuzzy logic for syndrome differential diagnosis is proposed. Based on this model, we implemented the system for diagnosing Eight rule diagnosis, organ diagnosis and then final differential syndrome of OTM. After carrying out inference process, the system will provide patient\`s syndromes differentiation diagnosis in the intervals and will give the explanation, which helps the user to understand the obtained conclusions.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2008년도 하계학술대회 논문집
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• pp.127-129
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• 2008

This paper describes a method of approximate reasoning for fuzzy control of servo system, based on decomposition of -level fuzzy sets. It is propose that logic circuits for fuzzy PI+PD are a body from fuzzy inference to defuzzificaion in cases where the output variable u directly is generated PWM. The effectiveness for robust and faster response of the fuzzy control scheme is verified for a variable parameter by comparison with a PID control and fuzzy control. A position control of DC servo system with a fuzzy logic controller successfully demonstrated.

• International Journal of Control, Automation, and Systems
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• 제4권1호
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• pp.17-29
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• 2006

A novel inverse kinematics solution based on the back propagation neural network (NN) for redundant manipulators is developed for online obstacles avoidance. A laser transducer at the end-effctor is used for online planning the trajectory. Since the inverse kinematics in the present problem has infinite number of joint angle vectors, a fuzzy reasoning system is designed to generate an approximate value for that vector. This vector is fed into the NN as a hint input vector rather than as a training vector to guide the output of the NN. Simulations are implemented on both three- and four-link redundant planar manipulators to show the effectiveness of the proposed position control system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.627-629
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• 1999

This paper presents a new FDI scheme based on dynamic fuzzy model(DFM) for the nonlinear system. The dynamic behavior of a nonlinear system is represented by a set of local linear models. The parameters of the DFM are identified in on-line and aggregated to generate a residual vector by the approximate reasoning. The neural network classifer learns the relationship between the residual vector and fault type and used both for the detection and isolation of process faults We apply the proposed FDI scheme to the FDI system design for a two-tank system and show the usefulness of the proposed scheme.