• 제목/요약/키워드: Fuzzy Division

검색결과 600건 처리시간 0.027초

A Study on Color Fuzzy Decision Algorithm in Video Object Segmentation

  • Byun, Oh-Sung;Moon, Sung-Ryong
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제4권2호
    • /
    • pp.142-148
    • /
    • 2004
  • In this paper, we propose the color fuzzy decision algorithm to face segmentation in a color image. Our algorithm can segment without the user's interaction by fuzzy decision marking. And it removes small parts such as a noise using wavelet morphology in the image obtained by applying the fuzzy decision algorithm. Also, it merges and chooses the face region in each quantization image through rough sets. This video object division algorithm is shown to be superior to a conventional algorithm.

Adaptive Fuzzy Control of Yo-yo System Using Neural Network

  • Lee, Seung-ha;Lee, Yun-Jung;Shin, Kwang-Hyun;Bien, Zeungnam
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제4권2호
    • /
    • pp.161-164
    • /
    • 2004
  • The yo-yo system has been introduced as an interesting plant to demonstrate the effectiveness of intelligent controllers. Having nonlinear and asymmetric characteristics, the yo-yo plant requires a controller quite different from conventional controllers such as PID. In this paper is presented an adaptive method of controlling the yo-yo system. Fuzzy logic controller based on human expertise is referred at first. Then, an adaptive fuzzy controller which has adaptation features against the variation of plant parameters is proposed. Finally, experimental results are presented.

퍼지 선형계획법 해법 및 퍼지 DEA에의 적용에 관한 연구 (A Study on a Solution Approach to Fuzzy Linear Programs and Its Application to Fuzzy DEA Models)

  • 임성묵
    • 산업경영시스템학회지
    • /
    • 제31권2호
    • /
    • pp.51-60
    • /
    • 2008
  • A solution method for fuzzy linear programs is proposed. A fuzzy linear program is converted to a crisp linear program with average indices being applied to the objective function and constraints. A comparative analysis between the proposed average index approach and the possibilistic approach is given. As an application example, the proposed method is applied to the linear programming model for fuzzy data envelopment analysis, and the result is compared with that of the possibilistic approach.

A Comparative Study on the Prediction of KOSPI 200 Using Intelligent Approaches

  • Bae, Hyeon;Kim, Sung-Shin;Kim, Hae-Gyun;Woo, Kwang-Bang
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제3권1호
    • /
    • pp.7-12
    • /
    • 2003
  • In recent years, many attempts have been made to predict the behavior of bonds, currencies, stock or other economic markets. Most previous experiments used the neural network models for the stock market forecasting. The KOSPI 200 (Korea Composite Stock Price Index 200) is modeled by using different neural networks and fuzzy logic. In this paper, the neural network, the dynamic polynomial neural network (DPNN) and the fuzzy logic employed for the prediction of the KOSPI 200. The prediction results are compared by the root mean squared error (RMSE) and scatter plot, respectively. The results show that the performance of the fuzzy system is little bit worse than that of the DPNN but better than that of the neural network. We can develop the desired fuzzy system by optimization methods.

애매 bi-군과 퍼지 bi-함수의 성질에 관한 연구 (On some properties of vague bi-groups and fuzzy bi-functions)

  • 장이채;김태균;이병제;김원주
    • 한국지능시스템학회논문지
    • /
    • 제20권3호
    • /
    • pp.356-361
    • /
    • 2010
  • M. Demirci[Vague groups, J. math. Anal. Appl. vol.230, pp. 142-156, 1999] studied the vague group operation on a crisp set as a fuzzy function and estabished the vague group structure on a crisp set. In this paper we consider bi-groups which are studied by A.A.A. Agboola and L.S. Akinola. And we also will define vague bi-groups and fuzzy bi-functions and we investigate some basic operations on the vague bi-group and fuzzy bi-functions.

Active TMD systematic design of fuzzy control and the application in high-rise buildings

  • Chen, Z.Y.;Jiang, Rong;Wang, Ruei-Yuan;Chen, Timothy
    • Earthquakes and Structures
    • /
    • 제21권6호
    • /
    • pp.577-585
    • /
    • 2021
  • In this research, a neural network (NN) method was developed, which combines H-infinity and fuzzy control for the purpose of stabilization and stability analysis of nonlinear systems. The H-infinity criterion is derived from the Lyapunov fuzzy method, and it is defined as a fuzzy combination of quadratic Lyapunov functions. Based on the stability criterion, the nonlinear system is guaranteed to be stable, so it is transformed to be a linear matrix inequality (LMI) problem. Since the demo active vibration control system to the tuning of the algorithm sequence developed a controller in a manner, it could effectively improve the control performance, by reducing the wind's excitation configuration in response to increase in the cost efficiency, and the control actuator.

Online Automatic Gauge Controller Tuning Method by using Neuro-Fuzzy Model in a Hot Rolling Plant

  • Choi, Sung-Hoo;Lee, Young-Kow;Kim, Sang-Woo;Hong, Sung-Chul
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 2005년도 ICCAS
    • /
    • pp.1539-1544
    • /
    • 2005
  • The gauge control of the fishing mill is very important because more and more accurately sized hot rolled coils are demanded by customers recently. Because the mill constant and the plasticity coefficient vary with the specifications of the mill, the classification of steel, the strip width, the strip thickness and the slab temperature, the variation of these parameters should be considered in the automatic gauge control system(AGC). Generally, the AGC gain is used to minimize the effect of the uncertain parameters. In a practical field, operators set the AGC gain as a constant value calculated by FSU (Finishing-mill Set-Up model) and it is not changed during the operating time. In this paper, the thickness data signals that occupy different frequency bands are respectively extracted by adaptive filters and then the main cause of the thickness variation is analyzed. Additionally, the AGC gain is adaptively tuned to reduce this variation using the online tuning model. Especially ANFIS(Adaptive-Neuro-based Fuzzy Interface System) which unifies both fuzzy logics and neural networks, is used for this gain adjustment system because fuzzy logics use the professionals' experiences about the uncertainty and the nonlinearity of the system. Simulation is performed by using POSCO's data and the results show that proposed on-line gain adjustment algorithm has a good performance.

  • PDF

Gabor 특징과 FSVM 기반의 연령별 얼굴 분류 (Age of Face Classification based on Gabor Feature and Fuzzy Support Vector Machines)

  • 이현직;김윤호;이주신
    • 한국항행학회논문지
    • /
    • 제16권1호
    • /
    • pp.151-157
    • /
    • 2012
  • 최근 영상처리기술과 컴퓨터과학의 발달로 연령변화에 따른 얼굴형상 분류 방법은 일반적인 주제가 되었다. 사람의 연령별 얼굴분류는 생물학적 유전자와 오랜 생활의 식습관으로 인하여 얼굴 형상이 변하기 때문에 통계적 형상만으로 예측하기란 쉽지 않다. 본 논문에서는 Gobor 특징과 fuzzy SVM 기법을 이용하여 연령대별 얼굴분류 기법을 제안하였다. Gabor 웨이블릿 함수는 얼굴의 특징벡터를 구하기 위하여 사용되고 연령대별 얼굴형상 구분이 애매모호한 문제를 해결하기 위해 fuzzy SVM 기법을 이용하여 연령별 소속 함수를 정의하였다. 제안한 방법으로 연령별 소속함수에 따른 얼굴 분류 실험을 수행하였고 제안한 방법의 타당성을 확인하였다.

Integrated GUI Environment of Parallel Fuzzy Inference System for Pattern Classification of Remote Sensing Images

  • Lee, Seong-Hoon;Lee, Sang-Gu;Son, Ki-Sung;Kim, Jong-Hyuk;Lee, Byung-Kwon
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • 제2권2호
    • /
    • pp.133-138
    • /
    • 2002
  • In this paper, we propose an integrated GUI environment of parallel fuzzy inference system fur pattern classification of remote sensing data. In this, as 4 fuzzy variables in condition part and 104 fuzzy rules are used, a real time and parallel approach is required. For frost fuzzy computation, we use the scan line conversion algorithm to convert lines of each fuzzy linguistic term to the closest integer pixels. We design 4 fuzzy processor unit to be operated in parallel by using FPGA. As a GUI environment, PCI transmission, image data pre-processing, integer pixel mapping and fuzzy membership tuning are considered. This system can be used in a pattern classification system requiring a rapid inference time in a real-time.

인공지능기반 AHP를 이용한 교통제어기 설계 (A Design of Artificial based Traffic Control System using Artificial Analytic Hierachy Process)

  • 진현수
    • 한국지능시스템학회:학술대회논문집
    • /
    • 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
    • /
    • pp.448-451
    • /
    • 2005
  • 교통의 혼잡량이라든가 공기의 쾌적도 둥을 측정할 때는 상징적인 정보량을 이용한 퍼지 센서 알고리즘을 사용한다. 그런데 퍼지 센서를 구현할 때는 몇 개의 상징적인 정보량을 퍼지 규칙으로서 종합하여 출력을 산출하는데 상징적인 정보량을 퍼지 규칙이라는 막연한 방법을 사용하므로서 정확하지 못한 결과를 산출할 수밖에 없다. 따라서 본 논문에서는 퍼지 규칙으로 퍼지 센서를 구현하는 방법이 아닌 계층 분석 방법이라는 분석적인 방법을 이용하여 퍼지 센서를 구현하였고 이를 검증하기 위하여 퍼지 규칙 방법의 괴지 센서와 계층 분석 방법의 퍼지 센서를 교통량 제어에 적용하여 많은 통과차량수의 검증을 통하여 비교하여 보았다.

  • PDF