• Journal of the Korean Institute of Navigation
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• v.18 no.2
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• pp.69-81
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• 1994

Studies on the ship's automatic navigation & berthing control have been continued by way of solving the ship's mathematical model, but the results of such studies have not reached to our satisfactory level due to its non-linear characteristics at low speed. In this paper, the authors propose a new berthing control system which can evaluate as closely as cap-tain's decision-making by using the FNN(Fuzzy Neural Network) controller which can simulate captain's knowledge. This berthing controller consists of the navigation subsystem FNN controller and the berthing subsystem FNN controller. The learning data are drawn from Ship Handling Simulator (NavSim NMS-90 MK Ⅲ) and represent the ship motion characteristics internally. According to learning procedure, both FNN controllers can tune membership functions and identify fuzzy control rules automatically. The verified results show the FNN controllers effective to incorporate captain's knowledge and experience of berthing.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1094-1096
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• 1998

An intelligent power transformer protective relaying algorithm based on fuzzy decision-making is proposed. To distinguish external faults with CT saturation, overexcitation and inrush conditions from internal faults, a newly designed fuzzy-rule base is used. The Dempster-Shafer's rule of combition is used for fuzzy inference. A series of the S/W and H/W tests show the proposed protection algorithm has practically sufficient sensitivity and selectivity.

• Journal of Convergence Society for SMB
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• v.3 no.1
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• pp.23-30
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• 2013

In this paper, fuzzy entropy and similarity measure to measure the uncertainty and similarity of data as real value were introduced. Design of fuzzy entropy and similarity measure were illustrated and proved. Obtained measures were applied to the calculating process and discussed. Extension of data quantification results such as decision making and fuzzy game theory were also discussed.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.24-29
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• 2013

In this paper, we propose a fuzzy inference model for a navigation algorithm for a mobile robot that intelligently searches goal location in unknown dynamic environments. Our model uses sensor fusion based on situational commands using an ultrasonic sensor. Instead of using the "physical sensor fusion" method, which generates the trajectory of a robot based upon the environment model and sensory data, a "command fusion" method is used to govern the robot motions. The navigation strategy is based on a combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance based on a hierarchical behavior-based control architecture. To identify the environments, a command fusion technique is introduced where the sensory data of the ultrasonic sensors and a vision sensor are fused into the identification process. The result of experiment has shown that highlights interesting aspects of the goal seeking, obstacle avoiding, decision making process that arise from navigation interaction.

• Journal of Information Management
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• v.24 no.4
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• pp.43-57
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• 1993

This paper discusses the basic concept of artificial intelligence(AI) and expert system and a particular technique(fuzzy logic) applied to expert systems. It examines expert system as search intermediaries during the past few years, particularly in terms of the following functions: 1) handling certain classes of questions on a particular database, 2) assisting in decision making for selecting databases or search terms, and 3) offering advice while keeping the end-user in the control of the searching process. The limitations and difficulties involved in developing such expert systems are also presented.

• Journal of Korean Port Research
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• v.7 no.2
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• pp.61-68
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• 1993

Studies on the ship's automatic navigation & berthing control have been continued by way of solving the ship's mathematical model, but the results of such studies have not reached to our satisfactory level due to its non-linear characteristics at low speed. In this paper, the authors propose a new control system which can evaluate as closely as captain's decision-making by using the FNN(Fuzzy Neural Network) controller which can simulate captain's knowledge. This controller contains the concept of safety according to channel width. The learning data are drawn from ship Handling simulator(NavSim NMS-90 MK III) and represent the ship motion characteristics internally. According to learning procedure, the FNN controller can tune membership functions and identify fuzzy control rules automatically. The verified results show that the FNN controller is effective to incorporate captain's knowledge and experience of manoeuvrability in channel.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.1039-1042
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• 2008

Wireless sensor networks enable pervasive, ubiquitous, and seamless communication with the physical world. In this paper, we are concerned for clustering sensors into groups, so that sensors communicate information only to cluster heads and then the cluster heads communicate the aggregated information to the sink node, that the network can save energy. In this paper, we propose the algorithm for electing the cluster head and fuzzy registration of cluster head in a dynamic cluster wireless sensor networks. For making decision for clustering we will use fuzzy logic system. In simulation, we could achieve power regulation of total consumption and also the stabilization of the networks energy efficiency.

• Journal of Internet Computing and Services
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• v.8 no.1
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• pp.1-14
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• 2007

IF handoff events are occurred during the transmission of multimedia traffic, the efficient resource allocation and handoff procedures are necessary to maintain the same QoS of transmitted multimedia traffic because the QoS may be defected by some delay and information loss, This paper proposes a handoff scheme to accommodate multimedia traffic based on the resource reservation procedure using direction estimation, This scheme uses a novel mobile tracking method based on Fuzzy Multi Criteria Decision Making, in which uncertain parameters such as PSS (Pilot Signal Strength), the distance between the mobile and the base station, the moving direction, and the previous location are used in the decision process using the aggregation function in fuzzy set theory, With the position information, the moving direction is determined, The handoff requests for real time sessions are handled based on the direction prediction and the resource reservation scheme, The resources in the estimated adjacent cells should be reserved and allocated to guarantee the continuity of the real time sessions, Through simulation results, we show that our proposed resource reservation method provides a better performance than that of the conventional 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.5-8
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• 2003

This paper presents a methodology to be able to select an appropriate RP system that suits the end use of a part. Evaluation factors used in process selection include major attributes such as accuracy, roughness, strength, elongation, part cost and build time that greatly affect the performance of RP systems. Crisp values such as accuracy and surface roughness are obtained with a new test part developed. The test part is designed with conjoint analysis to reflect users' preference. The part cost and build time that have approximate ranges due to cost and many variable parameters are presented by linguistic values that can be described with triangular fuzzy numbers. Based on the evaluation values obtained, an appropriate RP process for a specific part application is selected by using the modified TOPSIS(Technique of Order Preference by Similarity to Ideal Solution) method. It uses crisp data as well as linguistic variables, and each weight on the alternatives is assigned by using pair-wise comparison matrix. The ranking order helps the decision making of the selection of RP systems.