• Journal of Korea Port Economic Association
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• v.27 no.2
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• pp.39-57
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• 2011

Recently Incheon Port and Pyeongtak·Dangjin Port called as Capital Region Ports have enjoyed ever-increasing cargo volumes. However, there is a lack of research on this region while plenty of outputs were suggested on mega hub and regional hub ports in terms of shipping companies and stakeholders' port choice criteria. To identify and evaluate the Capital Region Ports, this paper identifies the factors and sub-components influencing their port choice and presents a structure for evaluating them. Based on the literature related to port selection and competition, a regional survey employed Factor Analysis to reveal that 'port facility and link', 'cost and service', 'port hinterland' and 'information service and port operation policy' are the determining factors in these regions. From the overall evaluation using Fuzzy Theory, Port of Incheon Port obtained high score compare to that of Port of Pyeongtak Dangjin.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.367-372
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• 2001

This paper proposes a hierachically structured navigation algorithm for multiple mobile robots under unknown dynamic environment. The proposed algorithm consists of three basic parts as follows. The first part based on the fuzzy rule generates the turning angle and moving distance of the robot for goal approach without obstacles. In the second part, using both fuzzy and neural network, the angle and distance of the robot to avoid collision with dynamic and static obstacles are obtained. The final adjustment of the weighting factor based on fuzzy rule for moving and avoiding distance of the robots is provided in the third stage. Some simulation results show the effectiveness of the proposed algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.54-60
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• 2002

In this paper, we proposed a hybrid neural network-fuzzy controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of loaming a inverse model neural network of Plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed speed controller get a good response compare with a neural network controller. We implemented the controller using the DSP processor and applied in a hydraulic servo system. And then we observed an experimental results.

• Journal of Korea Water Resources Association
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• v.44 no.11
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• pp.903-913
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• 2011

In this paper important factors in determining improvement priorities for water pipes were categorized into the effects of a pipe failure to entire pipe network and the characteristics of individual pipe. Subsequently, mathematical models that can quantify these factors were developed using the Fuzzy techniques. The effects of a pipe failure to entire pipe network and the characteristics of individual pipe that were estimated byFuzzy techniques were coined as Fuzzy Importance Index and Fuzzy Characteristic Index, respectively. The Fuzzy Characteristic Index was further categorized into Fuzzy Deterioration Index and Fuzzy Difficulty Index. Considerations were given to applying weights to specific factors in the developed model depending on the circumstances of model applications. To provide an example of the methodology an example pipe network, Net3, of the EPANET program was used. The Fuzzy Importance Index (FII) and Fuzzy Deterioration Index (FDI) were calculated for the Net3 network by considering the hydraulic effects of a pipe failure on the entire pipe network and the pipe deterioration as one of the individual pipe characteristics. Subsequently, the improvement priorities of the pipes in the Net3 pipe network were established based on the FII and FDI.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.181-189
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• 2013

In this paper, we introduce the fuzzy neural network based on the individual input space to design the pattern recognizer. The proposed networks configure the network by individually dividing each input space. The premise part of the networks is independently composed of the fuzzy partition of individual input spaces and the consequence part of the networks is represented by polynomial functions. The learning of fuzzy neural networks is realized by adjusting connection weights of the neurons in the consequent part of the fuzzy rules and it follows a back-propagation algorithm. In addition, in order to optimize the parameters of the proposed network, we use real-coded genetic algorithms. Finally, we design the optimized pattern recognizer using the experimental data for pattern recognition.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.451-452
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• 2007

본 논문에서는 다항식 기반 Radial Basis Function(RBF)신경회로망(Polynomial based Radial Basis Function Neural Networks)을 설계하고 이를 2-클래스 패턴 분류 문제에 응용하여 그 성능을 분석한다. 제안된 다항식기반 RBF 신경회로망은 입력층, 은닉층, 출력 층으로 이루어진다. 입력층은 입력 벡터의 값들을 은닉 층으로 전달하는 기능을 수행하고 은닉층은 Fuzzy c-means 클러스터링을 통하여 뉴런의 출력 값으로 내보낸다. 은닉층과 출력층사이의 연결가중치는 상수, 선형식 또는 이차식으로 이루어지며 경사 하강법에 의해 학습된다. Networks의 최종 출력은 연결가중치와 은닉층 출력의 곱에 의해 퍼지추론의 결과로서 얻어진다. 제안된 다항식기반 RBF 신경회로망은 각기 다른 4종류의 2-클래스 분류 문제에 적용 및 평가되어 분류기로써의 성능을 분석한다.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2050-2060
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• 1998

Weighting strategy is one of the necessary control strategies in automated reasoning to solve problecs within allowable time and computer memory. But, the strategy still consumes too much time since it depends soly on the user's experience and needs much of the user's manual work at each stage. This research suggests a tool which automates the weighting system to generate the weighting thesaurus and merges it to the mechanical theorem prover.

• Journal of Korean Society of Steel Construction
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• v.9 no.4 s.33
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• pp.579-588
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• 1997

During the construction of cable stayed bridge, errors are always caused by various reasons, accumulated and amplified through the complex construction steps. It is likely that the undesirable stress distribution of members and the large deflection of the bridge different from design values come out The adjustment of cables during construction is absolutely indispensable to correct the stress distribution of the members and the geometrical configuration of the bridge. In the conventional method, weight coefficients are used to consider the difference of units between cable forces and girder deflections during the optimization process of cable adjustment. However, it is not easy to determine weight coefficients and the adjustment must be repeated several times with the time consuming process of the determination of new weight coefficients in case that errors are out of design allowable limits. In this paper, fuzzy linear regression analysis is applied to the cable adjustment to overcome those problems. In the application of fuzzy linear regression analysis method the designer's intention and the design allowable limits can be formulated in the form of the constraints of the linear optimization problem. Therefore, the cable adjustment in construction site can be carried out with the fuzzy linear regression analysis more rapidly than with the convetional method.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.227-227
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• 2012

본 연구는 수자원계획 문제에서 다기준 의사결정기법을 적용할 때 발생할 수 있는 두 가지 문제에 대해 분석하였다. 첫 번째는 다기준 의사결정기법 선택의 차이가 결과에 어느 정도 영향을 미칠 수 있는지를 제시하였고 두 번째는 평가기준에 대한 가중치와 대안들의 평가치에 대한 불확실성을 최소화하기 위해 민감도 분석을 수행하는 절차를 제시하였다. 첫 번째 문제를 위해 가중합계법, Compromise Programming, 계층화분석과정, 수정된 계층화 분석과정, 가중곱방법, TOPSIS, ELECTRE-2, Regime 방법을 사용하였다. 또한 최근 사용빈도가 높은 삼각형 Fuzzy 숫자와 다기준 의사결정기법을 결합한 기법에 대해서도 분석하였는데 Fuzzy WSM, Fuzzy 계층화분석과정, Fuzzy 수정 계층화분석과정, Fuzzy TOPSIS, Fuzzy Compromise Programming을 검토하였다. 분석결과 평가기준에 대한 가중치 조건과 표준화 방법이 동일한 상황에도 불구하고 조금씩 다른 순위를 제시하는 것으로 나타났다. 또한 다양한 MCDM 기법들을 적용해도 동일한 순위로 나타나는 대안들이 있었다. 따라서 다기준 의사결정기법을 사용한 수자원 관리계획을 수립할 때에는 다양한 분석기법을 활용해서 기법의 선택으로 인한 불확실성을 최소화해야 한다. 두 번째 문제는 평가기준에 대한 가중치와 대안의 효과 정량화 자료의 불확실성을 극복하기 위해 각각에 대한 민감도 분석을 수행하였다. 본 연구는 유량확보와 수질개선을 위한 수자원 계획 수립을 위해 가중합계법을 이용한 문제에 두 경우의 민감도 분석을 모두 수행하였다. 이 과정에서 결정계수와 민감도 계수를 산정하여 이용하였다. 본 연구는 향후 수자원 관리 및 계획 분야에서 다기준 의사결정기법을 적용할 때 사용될 수 있는 기초 가이드라인이 될 것이다.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.89-96
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• 2000

Relevance feedback is a technique to learn the user's subjective perception of similarity between images, and has recently gained attention in Content Based Image Retrieval. Most relevance feedback methods assume that the individual features that are used in similarity judgments do not interact with each other. However, this assumption severely limits the types of similarity judgments that can be modeled In this paper, we explore a more sophisticated model for similarity judgments based on fuzzy measures and the Choquet Integral, and propose a suitable algorithm for relevance feedback, Experimental results show that the proposed method is preferable to traditional weighted- average techniques.