• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.69-78
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• 2015

Recently, research on the multi-agent system is developed actively in the various fields, especially on the control of complex system and optimization. In this study, we develop a multi-agent system for NPC simulation in game environment. The purpose of the development is to support quick and precise decision by inferencing the situation of the dynamic discrete domain, and to support an optimization process of the agent system. Our approach employed Petri-net as a basic agent model to simplify structure of the system, and used fuzzy inference engine to support decision making in various situation. Our experimentation describes situation of the virtual battlefield between the NPCs, which are divided two groups, such as fuzzy rule based agent and automata based agent. We calculate the percentage of winning and survival rate from the several simulations, and the result describes that the fuzzy rule based agent showed better performance than the automata based agent.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.123-129
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• 2000

This paper addresses a new double detection algorithm which is based on the fuzzy control in the adaptive echo canceller of communication system. In this method, the two input of the fuzzy inference for detecting double talk condition are used. The one is the cross-correlation coefficient between the error signal and the primary signal which is the summed signal of the real echo signal and the near-end signal. The other is the cross-correlation coefficient between the estimation error signal and the primary signal. The fuzzy controller made a fuzzification for two inputs by the membership functions of trapezoid and them became the composition using inference rules. The composed result is defuzzificated by the center gravity method. The output is compared with two threshold values to detect double talk and echo path variation effectively. It is confirmed by computer simulation that this fuzzy double talk detector is able to track echo path variation accurately.

• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.1
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• pp.3-12
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• 1994

본 연구는, 복잡한 비선형시스템의 표현에 뛰어난 능력을 갖고 있는 TSK형 퍼지모델로 부터 전체시스템의 안정성을 보장할 수 있는 퍼지상태제어기의 설계방법을 제안한다. 그 퍼지상태제어기는 TSK형 퍼지모델과 같은 형태의 퍼지규칙들로 구성되며, 추론 방법 및 상태제어 파라미터 행렬을 구하는 방벙은 전체시스템의 상태천이행렬이 원하는 안정한 것이 될 수 있도록 정해진다. 또한 본 논문에서는, 현재 대부분이 숙련가에 의해 수동으로 조작되고 있는 컨테이너 크래인의 새로은 제어 방법을 제시하고 제안한 퍼지상태제어기를 적용한다.컨테이너 크래인의 모형을 만들어, 제어숙련가의 수동조작으로 결정되는 트롤리와 승강기의 규범속도를 퍼지모델로 표현하고, 트롤리와 승강기가 그 규범 속도에 따르도록 제안한 퍼지상태제어기로 제어한다. 제안된 방법을 실험한 결과 모형크레인의 궤적이 숙련가에 의해 만들어진 궤적과 매우 유사하게 됨을 알 수 있었다.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.545-557
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• 2001

In this paper we propose a hierarchical classification algorithm based on rough membership function which can reason a new object approximately. We use the fuzzy reasoning method that substitutes fuzzy membership value for linguistic uncertainty and reason approximately based on the composition of membership values of conditional sttributes Here we use the rough membership function instead of the fuzzy membership function It can reduce the process that the fuzzy algorithm using fuzzy membership function produces fuzzy rules In addition, we transform the information system to the understandable minimal decision information system In order to do we, study the discretization of continuous valued attributes and propose the discretization algorithm based on the rough membership function and the entropy of the information theory The test shows a good partition that produce the smaller decision system We experimented the IRIS data etc. using our proposed algorithm The experimental results with IRIS data shows 96%~98% rate of classification.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.406-409
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• 2002

본 논문에서는 문자인식이 가능하도록 줌, 포커스를 제어하여 한글 문서 영상을 확대/축소하는 시스템을 구현하였다. 한글 문서 영상에서 확대/축소 할 영역이 지정되면 그 영역의 가로, 세로 거리를 펄스 수로 변환한 후 Step모터를 제어하여 그 위치만큼 카메라를 이동시킨다. 문서 영상이 입력되면 문자인식이 가능한 크기만큼 줌을 제어하고, 피드백 되어진 영상으로부터 조정된 줌에 맞는 포커스로 근접 제어한 후, 더욱 선명한 영상을 얻기 위해 명암 차이에 의한 미세 조정을 하였다. 이 경우, 줌 및 포커스는 퍼지 추론으로 .제어하는 DC모터로 조정하였다.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.1-9
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• 2008

Fuzzy Cognitive Map, one of ways to model, describe and infer reasoning relations, is widely used in the field of reasoning knowledge engineering. Despite of the natural and easy understanding of decision and smooth explanation of relation between front and rear, reasoning relation is organized with mathematical haziness and complex algorithm and rarely has an interactive user interface. This paper suggests an interactive Fuzzy Cognitive Map(FCM) construction support system. It builds a FCM increasingly concerning multiple experts' knowledge. Futhermore, it supports user-supportive environment by dynamically displaying the structure of Fuzzy Cognitive Map which is constructed by the interaction between experts and the system.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.120-125
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• 2005

In this paper, We propose the fuzzy controller for the gain tuning of PID controller The proposed controller doesn't use the crisp output error and rule tables though with a fuzzy inference process in forward fuzzifier, New Fuzzy PID Controller assigns relations and ranges of two variables of PID gain parameters. These new gain parameters are calculated by the fuzzy inference with max-min ranges of Kp and Kd. The Ki parameter is computed automatically between Kp and Kd parameter Is calculated by Ziegler-Nickels tuning rules. Finally we experimented the propose controller by the hydraulic servo motor control system. We can obtained desired results through the good control characteristics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.35-36
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• 2012

The generation of fuzzy rules is inevitable in order to construct fuzzy modeling and in general, has the problem that the number of rules increases exponentially with increasing dimension. To solve this problem, we introduce the system that generate the fuzzy rules and make a inference based on FCM clustering algorithm that partition the input space in the scatter form. The parameters in the premise part of the fuzzy rules is determined as membership matrix by the FCM clustering algorithm and the consequence part of the fuzzy rules is are expressed as a polynomial function. Proposed model evaluated using the numerical data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.439-447
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• 2011

It is a main concern for sustainable development in water resources management to evaluate adaptation capability of water resources structures under the future climate conditions. This study introduced the Fuzzy Inference System (FIS) to represent the change of release and storage of reservoirs in the Han River basin corresponding to various inflows. Defining the adaptation capability of reservoirs as the change of maximum and/or minimum of storage corresponding to the change of inflow, the study showed that Gangdong Dam has the worst adaptation capability on the variation of inflow, while Soyanggang Dam has the best capability. This study also constructed an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the more accurate and efficient simulation of the adaptation capability of the Soyanggang Dam. Nine Inflow scenarios were generated using historical data from frequency analysis and synthetic data from two general circulation models with different climate change scenarios. The ANFIS showed significantly different consequences of the release and reservoir storage upon inflow scenarios of Soyanggang Dam, whilst it provides stable reservoir operations despite the variability of rainfall pattern.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.139-148
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• 1995

In this paper an electro-hydraulic servo system is designed by using a fuzzy control algorithm. In order to drive an optimal fuzzy control system, a simulation program for the control system has been developed. By this program the fuzzifier and defuzzifier, a fuzzy inference method, a fuzzy relational matrix, and a fuzzy inference method are investigated. As a result, Larsen inference method, 9*9 fuzzy relational matrix, and center of area defuzzifier are turned out the best as parameters. Finally this method is compared with the conventional PID algotithm, and showed that the fuzzy control performs better than PID algorithm. The fuzzy control performs very well adap- tation against uncertain disturbances.