• Title/Summary/Keyword: Fuzzy factor

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Obesity Evaluation System using Fuzzy Inference (퍼지추론을 이용한 비만평가 시스템)

  • Jeong Gu-Beom;Kim Doo-Ywan
    • Journal of Internet Computing and Services
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    • v.4 no.2
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    • pp.61-67
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    • 2003
  • It has recently become known that the social issue of obesity, caused by increased caloric intake and lack of exercise, is a risk factor in the cause of various adult diseases. Above all, to prevent or cure obesity, we must accurately evaluate the degree of obesity, and we have used BML, WHR, and waist measurements for this purpose. In this paper, we propose an obesity evaluation system based on fuzzy inference using BML and waist measurement. For this purpose, we decided reasoning rule and membership function about BML and waist measurements. The inference result is presented in a descriptive sentence.

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A Sutdy on Improvement of Geomeric Accuracy by using Fuzzy Algorithm in Surface Grinding (퍼지 알고리즘을 이용한 평면연삭의 형상정도 향상에 관한 연구)

  • 천우진;김남경;하만경;송지복
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1993.10a
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    • pp.149-154
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    • 1993
  • In heavy grinding that is on of the high efficient grinding method, meaningful deformation is generated by high temperature. So, after machining, geomeric error generated od the workpiece. The most important factor on the geometric error is temperature difference between upper layer and lower layer (T $_{d}$) . Relations between Td and grinding condition and maximum geometric error and grinding condition are obtained by experiment. This relations are used in fuzzy algorithm for improvement geometric accuracy. The main results are follows : (1) The linear relation between maximum geometric error and grinding condition is ovtained by experiment. (2) The linear relation between maximum temperature difference between upper layer and lower layer and grinding condition is ovtained by experiment. (3) Control peth of wheel for improvement geometric accuracy is obtained by using the fuzzy algorithm.m.

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Self-Tuning Fuzzy Logic Controller for a Dual Star Induction Machine

  • Merabet, Elkheir;Amimeur, Hocine;Hamoudi, Farid;Abdessemed, Rachid
    • Journal of Electrical Engineering and Technology
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    • v.6 no.1
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    • pp.133-138
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    • 2011
  • This paper proposes a simple but robust self-tuning fuzzy logic controller for the speed regulation of a dual star induction machine based on indirect field oriented control. For feed the two star of this machine, two voltage source inverters based on sinus-triangular pulse-width modulation techniques are introduced. The simulation results show the robustness and good performance of the proposed controller.

The Vibration Suppressible Method with Estimated Torsion Torque Feedback in Fuzzy Controller

  • Choo, Yeon-Gyu;Lee, Kwang-Seok;Kim, Hyun-Deok;Kim, Bong-Gi
    • Journal of information and communication convergence engineering
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    • v.6 no.4
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    • pp.421-424
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    • 2008
  • In torque transmission system, we must suppressed vibration for Accuracy characteristic response of motor, Therefore, vibration suppression factor is very important motor control. To suppress vibration, a various control method has been proposed. Specially, one method of vibration suppression used disturbance observer filter. This method is torsion torque passing disturbance observer filter. By the estimated torsion torque feedback, vibration can be suppressed. The CDM(coefficient diagram method) is used to design the filter and Proportional controller. But using coefficient diagram method, not adapted controller parameter in disturbance. For this solution, we used fuzzy controller for auto tuning controller parameter. We proved this approach is confirmed by simulation.

Fatigue Life Prediction using Fuzzy Reliability theory (퍼지신뢰성이론에 의한 피로수명 예측)

  • 심확섭;이치우;장건의
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.672-675
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    • 1995
  • Because of a sudden growth of the research of fatigue failure, recent machines or structures have been designed by damage tolerance design in many fields. Consequently, it is the most primary factor to clarity the specific character of fatique failure in the design of machines or structures considering reliability. A statistical analysis is required to analyze the outcome of an experiment or a life estimate by reason of that fatigue failure contains lots of random elements. Reliability analysis which has tukenn the place of the existing analyses in the consideration of the uncertainty of a material, is a very efficient way. Even reliability analysis, however, is not a perfect way to analyses the uncertainties of all the materials. This thesis would refer to a newly conceived data analysis that the coefficient of a system could cause the ambiguity of the relationship of an input and output.

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The Hybrid Fuzzy Controller using the Hybrid Auto-tuning Algorithm (하이브리드 자동 동조 알고리즘을 이용한 하이브리드 퍼지 제어기)

  • Lee, Dae-Keun;Kim, Joong-Young;Oh, Sung-Kwun
    • Proceedings of the KIEE Conference
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    • 1999.11c
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    • pp.521-523
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    • 1999
  • In this paper, we propose the hybrid fuzzy controller(HFC) and the hybrid auto-tuning algorithm. The proposed HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance such as sensitivity improvement in steady state and robustness in transient state than any other controller. In addition, a hybrid auto-tuning algorithm which consists of genetic algorithm and complex algorithm to automatically generate weighting factor, scaling factors and PID control gains optimizes the output of HFC. As an typical example of non-linear system in control theory an inverted pendulum will be controlled by the suggested HFC and illustrated the performance and applicability of this proposed method by simulation.

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Design of Combined Direct/Indirect Adaptive Neural Control System using Fuzzy Rule (퍼지규칙에 의한 직/간접 혼합 신경망 적응제어시스템의 설계)

  • Jang, Soon-Ryong;Choi, Jae-Seok;Lee, Soon-Young
    • Proceedings of the KIEE Conference
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    • 1999.07b
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    • pp.724-727
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    • 1999
  • In this paper, the direct and indirect neural adaptive controller are combined based on the Lyapunov synthesis approach. The proposed adaptive controller is constructed from RBF neural network and a set of fuzzy IF-THEN rules. And the weighting parameters are adjusted on-line according to some adaptation law for the purpose of controlling the plant to track a given trajectory. In this scheme, fuzzy IF-THEN rules are used to decide the combined weighting factor. It is shown that all the signals in the closed-loop system are uniformly bounded under mild assumptions. The effectiveness of the proposed control scheme is demonstrated through the control of one-link rigid robotics manipulator.

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SENSITIVITY ANALYSIS IN FUZZY RELIABILITY ANALYSISA

  • Onisawa, Takehisa
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10b
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    • pp.764-769
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    • 1988
  • In this paper the failure possibility and the error possibility are used to represent reliability of a technical component and that of a human operator, respectively. The failure possibility and the error possibility are fuzzy sets on the interval [0,1]. In a man-machine system, reliability of the technical component and that of the human operator are usually affected by many factors, e.g., the environment in which a machine is operated, psychological stress of the human operator, etc. The possibility is derived from not only the failure or the error rate but also estimates of these factors. The fuzzy reasoning plays an important role in the derivation. The reliability analysis is performed by the use of the possibility obtained by the present method. Moreover this paper discusses the sensitivity analysis which evaluates what extent the change of the estimation of each factor has an influence on reliability of a man-machine system. The important factors to be ameliorated are shown through the sensitivity analysis.

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Seismic Evaluation of Existing Buildings Based on Fuzzy Inference System (퍼지추론방식에 의한 기존시설물 내진성능평가)

  • 김남희;홍성걸;장승필
    • Journal of the Earthquake Engineering Society of Korea
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    • v.5 no.2
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    • pp.1-11
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    • 2001
  • 내진성능평가 시스템은 구조시스템의 합리적인 분류, 적절한 평가 기준, 그리고 종합적인 평가방법을 포함하여야한다. 외국의 현행 내진성능 평가방법은 데이터의 수집과 주요 평가 항목을 위한 약산식 그리고 평가 점수를 이용하여 전문가의 판단에 근거한 평가 방법을 제시하고 있다. 본 연구는 국내 건축구조물에 예비 내진평가 방법에 중점을 두고 퍼지추론 시스템에 근거한 내진평가방법의 전형을 개발한다. 평가항목의 위계는 건무의 수직, 수평방향을 불규칙성, 비대칭성, 여용성, 그리고 건물 연한을 포함한 전체적인 특성과 부재 단계에서의 상세한 평가 항목으로 구성한다. 퍼지추론방법에 대한 기존의 연구결과를 근허가혀 이용한 내진성능 평가방법에 적절히 적용하기 위하여 4가지 주요 모듈을 설정한다. (1) 퍼지 입력 (2) 퍼지에 근거한 규칙기반 (3) 퍼지추론, 그리고 (4) 퍼지출력으로 구성된다. 더욱이 개별적인 성능 수준에 종합적인 평가지수를 끌어내기 위하여 퍼지추론방법을 적용하였다.

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전문가 시스템의 불확실성 추론 방법

  • 이승재
    • 전기의세계
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    • v.39 no.8
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    • pp.7-12
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    • 1990
  • 전문가 시스템에 있어서의 불확실성 정보의 표현 및 처리를 담당하는 주요 추론모델중 Bayesian모델, Certainty Factor 모델 그리고 Dempster-Shafer 모델의 기본이론을 살펴보고자 한다. 이외의 주요 추론 방법으로서 Fuzzy추론 모델이 있는데 이는 판단 지식에 대한 주관적 불확실성과 "매우", "많이" 등의 자연어가 포함하고 있는 불분명성을 체계적이고 효과적으로 다룰 수 있는 Fuzzy Set 이론에 근거한 방법으로서, 불확실성 또는 불명료성을 0에서부터 1 사이의 값을 갖는 membership degree로 표시하며 이를 "MIN"과 "MAX" 함수를 이용한 합성 추론 규칙(Composition Rule of Inference)를 적용하여 처리한다. Fuzzy 추론 모델은 자연어를 포함하는 전문가의 지식 처리에 매우 적합하여 앞으로 그 응용이 높이 기대되는 방법이다. 이외에 Bayesian 모델을 변형 응용한 PROSPECTOR의 Likelyhood Ratio 모델, 정량적 방법인 Theory of Endorsement 모델 등 여러 방법이 있다. 그러나 어느 모델이 더 일반성을 갖고 더 좋은 방법인가 하는 문제에 대하여는 아직 많은 연구가 요구된다. 따라서 이러한 모델들의 전문가 시스템 적용에 있어서는 각 모델의 장단점을 고려하여 주어진 문제 영역에 적합한 모델을 선택하는 것이 바람직하다. 현재 불확실성 처리에 있어서 각 문제에 따른 경험적인 처리에 의존하는 전력 계통 분야의 적용에 있어서도 이러한 실인간 전문가의 추론방법에 근접된 반성을 갖는 불확실성 추론 방버 도입이 요구된다.가의 추론방법에 근접된 반성을 갖는 불확실성 추론 방버 도입이 요구된다.

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