• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.225-230
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• 1992

In this paper, a new learning fuzzy logic controller(LFLC) is presented. The proposed controller is composed of the main control part and the learning part. The main control part is a fuzzy logic controller(FLC) based on linguistic rules and fuzzy inference. For the learning part, artificial neural network(ANN) is added to FLC so that the controller may adapt to unknown plant and environment. According to the output values of the ANN part, which is learned using error back-propagation algorithm, scale factors of the FLC part are determined. These scale factors transfer the range of values of input variables into corresponding universe of discourse in the FLC part in order to achieve good performance. The effectiveness of the proposed control strategy has been demonstrated through simulations involving the control of an unknown robot manipulator with load disturbance.

• 한국전자파학회논문지
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• 제21권10호
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• pp.1194-1199
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• 2010

본 논문에서는 빔 성형(beamforming) 기술을 사용하는 릴레이 기반 셀룰러 네트웍에서, 순방향 링크 채널 상태에 대한 제한된 피드백 정보를 이용하여, 동시에 전송되는 송신기과 수신기 사이의 직접 링크(direct link)와 중계기(relay station)와 수신기 사이의 중계 링크(relaying link) 간의 간섭을 효과적으로 억제하는 간섭 회피(interference avoidance) 빔 성형 기술을 제안한다. 이를 위해 송신기는 빔 성형을 사용하여 한정된 공간으로만 직접링크 신호 전력을 전송하고, 송신기의 간섭 전력이 도달하지 않는 공간 영역에 위치한 릴레이들의 relaying을 허용함으로써, 효과적으로 직접 링크와 중계 링크간 간섭을 억제할 수 있는 충돌 회피(collision avoidance) 스케줄링 기술을 제안한다. 시뮬레이션을 통해 제안하는 간섭 회피 빔 성형 기술이 중계 링크의 전송 용량을 보장하면서 동시에 전송되는 직접 링크 전송 용량을 최대화 할 수 있음을 보인다.

• 융합보안논문지
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• 제15권1호
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• pp.83-89
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• 2015

다수의 CCTV(Closed Circuit Television)로 광범위한 지역을 관리하는 보안 감시 시스템에서 시간과 장소에 구애받지 않고 CCTV를 원격으로 실시간 모니터링 할 수 있도록 어플리케이션을 설계 및 구현했다. Xcode를 사용하여 개발된 어플리케이션은 폐쇄적인 중앙 관제 시스템으로부터 안전한 관리자 인터페이스를 제공하는 역할을 한다. 효율적이며 직관적인 인터페이스를 통해 어플리케이션은 중앙관제 시스템에서 제공하는 실시간 상황 알림보고 및 상황 인지 추론 결과를 원격의 관리자에게 전달한다. 사용자의 편의를 위해, 어플리케이션은 이벤트 발생시의 push 알림, SNS(Social Network Service) 연동을 포함한 다양한 기능을 제공한다. 실시간 모니터링을 위해 카메라의 화면을 스트림 해줄 서비스는 Wirecast와 Wowza media server를 이용한다. Wowza stream engine은 실시간 스트리밍을 돕는 개발규격에 맞춘 URL을 제공한다. 이를 통해 모바일에서 실시간 스트리밍 결과를 받아 볼 수 있으며, 그 과정에서 발생되는 자원 소모에 관련된 성능분석을 보였다.

• 한국멀티미디어학회논문지
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• 제20권11호
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• pp.1811-1819
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• 2017

As the induction motor is the core production equipment of the industry, it is necessary to construct a fault prediction and diagnosis system through continuous monitoring. Many researches have been conducted on motor fault diagnosis algorithm based on signal processing techniques using Fourier transform, neural networks, and fuzzy inference techniques. In this paper, we propose a fault diagnosis method of induction motor using LPC and DNN. To evaluate the performance of the proposed method, the fault diagnosis was carried out using the vibration data of the induction motor in steady state and simulated various fault conditions. Experimental results show that the learning time of our proposed method and the conventional spectrum+DNN method is 139 seconds and 974 seconds each executed on the experimental PC, and our method reduces execution time by 1/8 compared with conventional method. And the success rate of the proposed method is 98.08%, which is similar to 99.54% of the conventional method.

• 한국정보통신학회논문지
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• 제5권5호
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• pp.931-940
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• 2001

본 논문에서는 ATM 네트워크에서 예측할 수 없고 폭주가 가능한 입력의 트래픽 제어를 위한 Fuzzy Policing Mechanism(FPM)을 제안한다. FPM은 카운터, 감산기와 퍼지논리제어기(FLC)로 구성된다 FLC는 퍼지화기, 추론 엔진, 비퍼지화기로 구성된다. FLC의 출력은 감산기에 입력되어 카운터상태를 일정하게 조절하며 카운터는 셀의 전송을 제어하게 된다. 시뮬레이션에서는 Fluid Flow 방법에 의한 Leaky Bucket algorithm(LBM)과 FPM의 셀 손실 확률과 특성성능을 비교하였다. 시뮬레이션 결과, FPM은 LBM보다 작은 셀 손실 확률을 얻었으며 가변적인 트래픽 자원을 효율적으로 제어했다. 그리고 특성성능에서 FPM이 좋은 응답 특성 및 선택도를 보였다.

• Environmental Engineering Research
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• 제14권2호
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• pp.111-119
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• 2009

A prototype GIS-based decision support system (DSS) was developed by using a database management system (DBMS), a model management system (MMS), a knowledge-based system (KBS), a graphical user interface (GUI), and a geographical information system (GIS). The method of selecting a dispersion model or a modeling scheme, originally devised by Park and Seok, was developed using our GIS-based DSS. The performances of candidate models or modeling schemes were evaluated by using a single index(statistical score) derived by applying fuzzy inference to statistical measures between the measured and predicted concentrations. The fumigation dispersion model performed better than the models such as industrial source complex short term model(ISCST) and atmospheric dispersion model system(ADMS) for the prediction of the ground level $SO_2$ (1 hr) concentration in a coastal area. However, its coincidence level between actual and calculated values was poor. The neural network models were found to improve the accuracy of predicted ground level $SO_2$ concentration significantly, compared to the fumigation models. The GIS-based DSS may serve as a useful tool for selecting the best prediction model, even for complex terrains.

• 대한기계학회논문집
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• 제18권2호
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• pp.339-350
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• 1994

This paper presents a method for automatic generation of line balanced assembly sequences based on disassemblability and proposes a method of evaluating an assembly work time using neural networks. Since a line balancing problem in flexible assembly system requires a sophisticated planning method, reasoning about line balanced assembly sequences is an important field of concern for planning assembly lay-out. For the efficient inference of line balanced assembly sequences, many works have been reported on how to evaluate an assembly work time at each work station. However, most of them have some limitations in that they use cumbersome user query or approximated assembly work time data without considering assembly conditions. To overcome such criticism, this paper proposes a new approach to mathematically verify assembly conditions based on disassemblability. Based upon the results, we present a method of evaluating assembly work time using neural networks. The proposed method provides an effective means of solving the line balancing problem and gives a design guidance of planning assembly lay-out in flexible assembly application. An example study is given to illustrate the concepts and procedure of the proposed scheme.

• Fibers and Polymers
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• 제7권2호
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• pp.203-212
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• 2006

The purpose of this study was to examine the effects of the structural properties of plain knit fabrics on the subjective perception of textures, sensibilities, and preference among consumers. This study, then, aimed to provide useful information with respect to planning and designing knitted fabrics by predicting the subjective characteristics analyzed according to their structural properties. For this purpose, we employed statistical analysis tools, such as factor and regression analysis and an adaptive-network-based fuzzy inference system(ANFIS), thereby combining the merits of fuzzy and neural networks and presupposing a non-linear relationship. Through factor analysis, we also categorized the subjective textures into 'roughness', 'softness', 'bulkiness' and 'stretch-ability' with R2=70.32%: and categorized the sensibilities into 'Stable/Neat', 'Natural/Comfortable' and 'Feminine/Elegant' with R2=68.12%. We analyzed subjective textures, sensibilities, and preference with ANFIS, assuming non-linear relationships; consequently, we were able to generate three or four fuzzy rules using wool/rayon fiber content and loop length as input data. The textures of roughness and softness exhibited a linear relationship, but other subjective characteristics demonstrated a non-linear input-output relationship. Compared with linear regression analysis, the ANFIS exhibited had higher predictive power with respect to predicting subjective characteristics.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1998년도 춘계학술발표회논문집(1)
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• pp.264-270
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• 1998

This research broadens the prime concern of nuclear power plant operations from safe performance to both economic and safe performance. First emergency diesel generator is identified as one of main contributors for the lost plant availability through the review of plants forced outage records. The framework of an integrated architecture for performing modern on-line condition for operational availability improvement is configured in this work. For the development of the comprehensive sensor networks for complex target systems, an integrated methodology incorporating a structural hierarchy, a functional hierarchy, and a fault-system matrix is formulated. The second part of our research is development of intelligent diagnosis and maintenance advisory system, which employs Bayesian Belief networks (BBNs) as a high level reasoning tool incorporating inherent uncertainty use in probabilistic inference. Our prototype diagnosis algorithms are represented explicitly through topological symbols and links between them in a causal direction. As new evidence from sensor network development is entered into the model especially, our advisory of system provides operational advice concerning both availability and safety, so that the operator is able to determine the likely modes, diagnose the system state, locate root causes, and take the most advantageous action. Thereby, this advice improves operational availability

• 한국지능시스템학회논문지
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• 제10권3호
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• pp.194-202
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• 2000

본 논문에서는 여러 분야에서 널리 응용되고 있는 적응 뉴로-퍼지 시스템(ANFIS)에서의 효과적인 퍼지 규칙 생성 방법을 제안한다. 기존의 입력공간 그리드 분할을 이용한 ANFIS의 규칙 생성에 있어서는 얻어진 규칙의 수가 지수적으로 증가하는 단점이 있다. 이에, 본 연구에서는 조건부적인 FCM을 이용하여 입.출력 데이터이 특성을 잘 반영할 수 있는 클러스터를 구하고, 퍼지 균등화 방법을 적용하여 출력변수의 소속함수를 자동 생성하도록 하엿다. 이렇게 함으로서 적은 규칙 수를 갖으며서도 효율적인 퍼지 규칙을 얻을 수 있도록 하였다. 이들 방법의 유용함을 보이고자 트럭 후진제어와 Box-Jenkins의 가스로 데이터의 모델리에 적용하여 제안된 방법이 이전의 연구보다 좋은 결과를 보임을 알 수 있다.