• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.660-663
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• 2003

The advanced computer network technology enables connectivity of computers through an open network environment. There has been growing numbers of security threat to the networks. Therefore, it requires intrusion detection and prevention technologies. In this paper, we propose a network based intrusion detection model using Fuzzy Cognitive Maps(FCM) that can detect intrusion by the Denial of Service(DoS) attack detection method adopting the packet analyses. A DoS attack appears in the form of the Probe and Syn Flooding attack which is a typical example. The Sp flooding Preventer using Fuzzy cognitive maps(SPuF) model captures and analyzes the packet information to detect Syn flooding attack. Using the result of analysis of decision module, which utilized FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. The result of simulating the "KDD ′99 Competition Data Set" in the SPuF model shows that the Probe detection rates were over 97 percentages.

• 한국지능시스템학회논문지
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• 제5권2호
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• pp.70-78
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• 1995

입출력 데이터를 이용한 퍼지모델의 설정은 구조 설정과 변수 설정으로 나누어진다. 본 논문에서는 기존 방법의 문제점을 해결하고 퍼지모델의 이러한 구조와 변수를 설정하는 새로운 방법을 제안한다. 입출력 데이터가 주어지면, 후건부 변수는 선형성과연속성을 고려하여 휴(Hough) 변환과클러스터링 방법에 의해 각각 설정된다. 또한 경사 하강법(Gradient descent method)을 사용하여 퍼지모델 변수의 미세조정을 행한다. 마지막으로 단일 입출력 시스템에 대하여 시뮬레이션을 통해 제안된 방법의 유효성을 보인다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.1854-1855
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• 2006

In this paper, the Takagi-Sugeno (TS) fuzzy state estimation scheme, which is suggested for a steady state estimator using standard Kalman filter theory with uncertainties. In that case, the steady state with uncertain can be represented by the TS fuzzy model structure, which is further rearranged to give a set of uncertain linear model using standard Kalman filter theory. And then the unknown uncertainty is regarded as an additive process noise. To optimize fuzzy system, we utilize the genetic algorithm. The steady state solutions can be found for proposed linear model then the linear combination is used to derive a global model. The proposed state estimator is demonstrated on a truck-trailer.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.138-138
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• 2000

In this paper, a methodology for designing a controller based on inverse dynamics for speed control of DC motors is presented. The proposed controller consists of a prefilter, the inverse dynamic model of a system and a fuzzy logic controller. The prefilter prevents high frequency effects from the inverse dynamic model. The model of the system is characterized by a nonlinear equation with coulomb friction. The fuzzy logic controller regulates the error between the set-point and the system output which may be caused by disturbances and it simultaneously traces the change o( the reference input. The parameters of the model are estimated by a genetic a]gorithm. An experimental work on a DC motor system is carried out to illustrate the performance of the proposed controller

• Communications for Statistical Applications and Methods
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• 제15권4호
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• pp.517-530
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• 2008

본 논문은 시간의 흐름에 따라 일정한 간격으로 관측된 시계열자료에 대한 통계적인 관계를 추정하기 위하여 삼각퍼지수를 이용한 퍼지시계열모형을 소개한다. 모든 관측치를 포함하는 전체집합을 분할하는 구간을 자료의 빈도수에 따라 결정하고 연속되는 두 시점에서 퍼지수가 일치하는 경우에는 관측된 자료의 차에 대한 정보를 이용하여 제안된 퍼지시계열모형을 추정한다. 예제를 이용하여 제안된 퍼지시계열모형의 정확성을 일반적인 시계열모형과 여러 가지 방법으로 추정된 퍼지시계열모형과 비교한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
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• pp.315-318
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• 2003

A systematic output-tracking control design technique for robust control of Takagi-Sugeno (T-S) fuzzy systems with norm-bounded uncertainties is developed. The uncertain T-S fuzzy system is first represented as a set of uncertain local linear systems. The tracking problem is then converted into the stabilization problem for a set of uncertain local linear systems thereby leading to a more feasible controller design procedure. A sufficient condition for robust asymptotic output tracking is derived in terms of a set of linear matrix inequalities (LMIs). A stability condition on the traversing time-instances is also established. The output tracking control simulation for a flexible-joint robot-arm model is demonstrated, to convincingly show the effectiveness of the proposed system modeling and controller design method.

• 한국위성정보통신학회논문지
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• 제12권3호
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• pp.35-40
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• 2017

위성의 상태를 파악하기 위해 기존에는 OOL(Out-Of-Limit) 방식을 많이 사용하여 왔다. OOL은 특정 텔레메트리의 상위, 하위 문턱 값을 지정하여 해당 값을 벗어날 경우 문제가 발생한 것으로 인식 하는 방식이다. 이 방법은 파라미터의 특성을 파악하여 각각의 문턱 값을 정확히 설정해야 하는 전문 지식과 노력이 필요하고 텔레메트리 값이 문턱값 내에서 비정상적으로 변할 경우는 검출할 수 없다는 문제점이 있다. 이러한 문제를 극복하기 위해 본 논문에서는 위성이 정상 상태일 때 텔레메트리의 통계적 특징 중 러프집합을 이용하여 중요한 것을 선택, 적용하여 퍼지 모델을 구축하고 이상 상태를 구분하는 시스템을 제안한다. 정상 상태의 데이터만 이용하여 모델을 구축하기 때문에 출력값을 비교 하여 사전에 정의되지 않은 비정상 상태의 구분이 가능 하며 다양한 통계 값을 이용하기 때문에 전문 지식 필요 없이 문턱값 내에서 비정상적으로 변하는 텔레메트리를 검출할 수 있다. 제안한 시스템의 동작 확인을 위해 실제 저궤도 관측위성의 배터리 온도 텔레메트리를 적용하여 시험을 수행 하였고 비정규적 운영 상태에 대한 검출이 성공적으로 이루어 졌다.

• Journal of Advanced Marine Engineering and Technology
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• 제18권3호
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• pp.85-93
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• 1994

A new diagnosis method is developed in this paper, in which the fuzzy set theory is introduced to diagnose the defects of rolling element bearings. The selection of membership function and the fuzzy operation model are discussed in detail here. The system is successfully used for various defects diagnosis of rolling element bearings.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1203-1206
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• 1993

Fuzzy techniques are applied to the positioning of an elastic beam. The advantage is that the system model is not needed. A simple fuzzy friction compensator is also used. The final position is achieved within 3/2 the period of the fundamental mode. A fuzzy set of rules is applied for large-angle positioning, with adaptations that reduce the effects of shock. In this case, the final position is achieved within two fundamental periods. There is typically some final error attributed to the dry friction.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.433-436
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• 2004

In this paper, we introduce a new Fuzzy Polynomial Neural Networks (FPNNS)-like structure whose neuron is based on the Fuzzy Set-based Fuzzy Inference System (FS-FIS) and is different from that of FPNNS based on the Fuzzy relation-based Fuzzy Inference System (FR-FIS) and discuss the ability of the new FPNNS-like structure named Fuzzy Set-based Polynomial Neural Networks (FSPNN). The premise parts of their fuzzy rules are not identical, while the consequent parts of the both Networks (such as FPNN and FSPNN) are identical. This difference results from the angle of a viewpoint of partition of input space of system. In other word, from a point of view of FS-FIS, the input variables are mutually independent under input space of system, while from a viewpoint of FR-FIS they are related each other. The proposed design procedure for networks architecture involves the selection of appropriate nodes with specific local characteristics such as the number of input variables, the order of the polynomial that is constant, linear, quadratic, or modified quadratic functions being viewed as the consequent part of fuzzy rules, and a collection of the specific subset of input variables. On the parameter optimization phase, we adopt Information Granulation (IC) based on HCM clustering algorithm and a standard least square method-based learning. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized FSPNN (gFSPNN), the model is experimented with using the time series dataset of gas furnace process.