• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.28-32
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• 2000

인터넷의 대중화와 더불어 전자상거래에 대한 관심과 중요성이 더욱 증대되고 있다. 전자상거래에서 보다 많은 고객들을 유치하기 위해서는 거래의 안정성 보장, 시스템의 사용 편의성, 다양한 물품의 제공, 저렴한 가격 등과 함께 차별화된 고객 서비스 전략이 필요하다. 고객의 취향에 적합한 상품 정보를 제공함으로써 고객의 만족도를 증진시키고 나아가 지속적인 방문을 유도하고자 한다. 본 논문에서는 고객이 전자상거래 쇼핑몰을 방문시 고객별로 관리되는 선호도를 활용하여 고객의 취향에 적합한 상품 정보를 제공한다. 퍼지논리를 이용하여 제품군간에 근접도를 반영함으로서 사용자에게 보다 좋은 상품 정보를 제공하는 기법을 제안한다.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.4
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• pp.115-124
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• 2014

Since it costs a lot to build a home network system of new service provider, the entry barrier is quite high. If it would be possible to build a home network system with high performance at a low building cost, it would be quite attractive. If a home network would be built in P2P-SIP(Peer to peer - Session Initiation Protocol) structure, it is possible to decrease server maintenance cost and keep high usability by deconcentrating the traffic concentrated on the server. It is also possible to efficiently manage the location information of terminal, if quorum system based on fuzzy logic would be applied. In this paper we propose the P2P-SIP structure applied of quorum system based on fuzzy logic by which a home network system can be built at low cost. It was possible to know by comparing the structure with existing one that the structure has very good performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.977-984
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• 2001

In this paper, Genetic-Fuzzy Algorithm for Inverted Pendulum is presented. This Algorithms is combine Fuzzy logic with the Genetic Algorithm. The Fuzzy Logic Controller is only designed to two inputs and one output. After Fuzzy control rules are determined, Genetic Algorithm is applied to tune the membership functions of these rules. To measure of performance of the designed Genetic-Fuzzy controller, Computer simulation is applied to Inverted Pendulum system. In the simulation, In the case of f[0.3, 0.3] Fuzzy controller is measured that maximum undershoot is $-5.0 \times 10^{-2}[rad]$, maximum undershoot is $3.92\times10^{-2}[rad]$ individually however, Designed algorithm is zero. The Steady state time is approximated that Fuzzy controller is 2.12[sec] and designed algorithm is 1.32[sec]. The result of simulation, Resigned algorithm is showed it's efficient and effectiveness for Inverted Pendulum system.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.153-159
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• 2009

The steel balls are core elements between inner part and outer part in a bearing system. The degree of goodness of the steel balls has been visually processed by human beings. In this paper we propose a new method that uses image processing algorithm and fuzzy logic theory. We use fuzzy inference engine and fuzzy Choquet integral algorithm in the proposed system. We first distinguish the defects of the steel balls by an image processing algorithm. And then the degree of the defects is classified by a fuzzy logic system. We perform some simulations to show the effectiveness and feasibility of the proposed system.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.736-741
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• 2001

The restoration optimum image from transformation image demands compound change of image change, calender reform, and multiple solution calculation. This study presents that system actively deal with outside interference, vibration, movement, mechanical feature on the operating or before the operating and avoids complicated mathematical numerical expression and revise based on expert knowledge based which applies Fuzzy Logic which is one of Artificial Intelligent technique.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.168-173
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• 2015

The flight control of aircraft, which has nonlinear time-varying dynamic characteristics depending on the various and unexpected external conditions, can be performed on two motions: longitudinal motion and lateral motion. In the longitudinal motion control of aircraft, pitch and trust are major control parameters and roll and yaw are control ones in the lateral motion control. Until now, a number of efficient and reliable control schemes that can guarantee the stability and maneuverability of the aircraft have been developed. Recently, the intelligent flight control scheme, which differs from the conventional control strategy requiring the various and complicate procedures such as the wind tunnel and environmental experiments, has attracted attention. In this paper, an intelligent longitudinal control scheme has been proposed utilizing Interval Type-2 fuzzy logic which can be recognized as a representative intelligent control methodology. The results will be verified through computer simulation with a F-4 jet fighter.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.342-347
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• 2003

It is essential to develop an algorithm for the estimate of link travel velocity and for the supply and control of travel information in the context of intelligent transportation information system. The paper proposes the fuzzy logic based prediction of link travel velocity. Three factors such as time, date and velocity are considered as major components to represent the travel situation. In the fuzzy modeling, those factors were expressed by fuzzy membership functions. We acquire position／velocity data through GPS antenna with PDA embedded probe vehicles. The link travel velocity is calculated using refined GPS data and the prediction results are compared with actual data for its accuracy.

• 전기의세계
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• v.39 no.12
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• pp.21-32
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• 1990

퍼지 논리를 이용한 제어시스템에 관하여 핵심 개념을 중심으로 기술하고자 한다. 요약컨데 이 퍼지제어기의 특징은 1) Parallel(distributed) control 2) logic control 3) linguistic control등이며 퍼지 제어가 효과적일 수 있는 제어대상(plant)로서는 수학적 모델을 적용하기 힘든 시스템으로서 경험적으로 또는 수동적인 방법으로 제어가 잘되고 있는 대상을 들 수 있다. 그 뿐만 아니라 간단한 제어기가 필요한 경우로서 보다 효과적인 제어측 Software를 쓰거나 센서 또는 필터없이 사용가능하고, Inverted Penedulum의 자세 제어처럼 정확성보다는 속도 응답 제어가 요구되는 경우 등에 효과적으로 쓸 수 있는 것으로 알려지고 있다. Fuzzy 제어는 지식 베이스의 규모에서 인공지능형 Expert System보다 Compact하고 선형.비선형 플랜트에 공히 이용될 수 있으며, 설계자는 오퍼레이터와의 접촉을 통해 룰을 구축하므로 사용자가 시스템을 이해하기 쉬운 잇점등이 있기도 한다. 그러나 가장 큰 문제는 구축해 놓은 시스템의 안전성(Stability)를 이론적으로 사전에 검증하기가 어렵고, 같은 제어대상이라 할지라도 추론방법, 소속함수의 형태선택, 룰수 등에 따라 제어성능이 바뀔수 있으나, 무엇이 어떤 영향을 주는지 규명되지 않은점 등 여러가지 연구되어야 할 내용이 많이 있다.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.17-23
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• 2016

In the future network such as Internet of Things (IoT), the number of computing devices are expected to grow exponentially, and each of the things communicates with the others and acquires information by itself. Due to the growing interest in IoT applications, the broadcasting in Opportunistic ad-hoc networks such as Machine-to-Machine (M2M) is very important transmission strategy which allows fast data dissemination. In distributed networks for IoT, the energy efficiency of the nodes is a key factor in the network performance. In this paper, we propose a fuzzy logic based probabilistic multi-hop broadcast (FPMCAST) algorithm which statistically disseminates data accordingly to the remaining energy rate, the replication density rate of sending node, and the distance rate between sending and receiving nodes. In proposed FPMCAST, the inference engine is based the fuzzy rule base which is consists of 27 if-then rules. It maps input and output parameters to membership functions of input and output. The output of fuzzy system defines the fuzzy sets for rebroadcasting probability, and defuzzification is used to extract a numeric result from the fuzzy set. Here Center of Gravity (COG) method is used to defuzzify the fuzzy set. Then, the performance of FPMCAST is evaluated through a simulation study. From the simulation, we demonstrate that the proposed FPMCAST algorithm significantly outperforms flooding and gossiping algorithms. Specially, the FPMCAST algorithm has longer network lifetime because the residual energy of each node consumes evenly.