• Title/Summary/Keyword: Fuzzy Structure

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Fuzzy r-minimal Continuous Functions Between Fuzzy Minimal Spaces and Fuzzy Topological Spaces

  • Min, Won-Keun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.10 no.2
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    • pp.124-127
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    • 2010
  • In this paper, we introduce the concepts of fuzzy r-minimal continuous function and fuzzy r-minimal open function between a fuzzy r-minimal space and a fuzzy topological space. We also investigate characterizations and properties for such functions.

Fuzzy Identification by means of Fuzzy Inference Method and Its Application to Wate Water Treatment System (퍼지추론 방법에 의한 퍼지동정과 하수처리공정시스템 응용)

  • 오성권;주영훈;남위석;우광방
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.6
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    • pp.43-52
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    • 1994
  • A design method of rule-based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of ``IF....,THEN...', using the theories of optimization theory , linguistic fuzzy implication rules and fuzzy c-means clustering. Three kinds of method for fuzzy modeling presented in this paper include simplified inference (type I), linear inference (type 2), and modified linear inference (type 3). In order to identify premise structure and parameter of fuzzy implication rules, fuzzy c- means clustering and modified complex method are used respectively and the least sequare method is utilized for the identification of optimum consequence parameters. Time series data for gas furance and those for sewage treatment process are used to evaluate the performance of the proposed rule-based fuzzy modeling. Comparison shows that the proposed method can produce the fuzzy model with higher accuracy than previous other studies.

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NOTE ON THE FUZZY PROXIMITY SPACES

  • Park, Kuo-Duok
    • Korean Journal of Mathematics
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    • v.10 no.2
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    • pp.131-140
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    • 2002
  • This paper is devoted to the study of the role of fuzzy proximity spaces. We define a fuzzy K-proximity space, a fuzzy R-proximity space and prove some of its properties. Furthermore, we discuss the topological structure based on these fuzzy K-proximity and fuzzy R-proximity.

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A Study on Selection of Effective Supplier and Analysis of Evaluation Structure in Supply Chain Management (공급체인 관리하에서 효율적인 협력업체 선정 및 평가구조 분석에 관한 연구)

  • Kim, Jin-Ho;Lee, Byoung-Ki
    • IE interfaces
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    • v.17 no.2
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    • pp.169-179
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    • 2004
  • In supply chain management, supplier capacity is very important to meet the customer demand quickly. This paper studies a supplier evaluation structure and then suggests a methodology using fuzzy theory for selecting an effective supplier. Several quantitative and qualitative evaluation factors should be analyzed in the evaluation structure. The qualitative factors includes not only product and service qualities but financial condition. The methodology deals with both the quantitative and qualitative factors together through fuzzy inference. A case study is also presented to show how to choose the best one among potential suppliers.

Hybrid Fuzzy Logic Controller using Modulation Function (변조함수를 이용하는 하이브리드 퍼지 논리 제어기)

  • Lee, Pyeong-Gi
    • Journal of the Korean Society of Industry Convergence
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    • v.6 no.4
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    • pp.393-399
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    • 2003
  • In this paper, a self-organizing fuzzy logic controller with hybrid structure is proposed. The structure of the proposed method is composed of a basic fuzzy logic controller and the FARMA SOC(Fuzzy Autoregressive Moving Average Self-organizing Controller). The self-organizing cntroller with hybrid structure has advantage over the FARMA controller as follows. The proposed controller improves poor performance due to the lack of I/O data to calculate predictive output. I executed some computer simulations on the regulation problem of an inverted pendulum system and compared the results of the proposed method with those of the FARMA SOC method.

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Multi-Mobile Robot System with Fuzzy Rule based Structure in Collision avoidance (충돌회피환경에서의 퍼지 규칙 기반 멀티 모바일 로봇 시스템)

  • Kim, Dong-W.;Yi, Chong-Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.3
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    • pp.233-238
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    • 2010
  • This paper describes a multi-mobile robot system with fuzzy rule based structure in collision avoidance. Collision avoidance is an important function to perform a given task collaboratively and cooperatively in multi-mobile robot environments. So the important but challenging problem is handled in this paper. Considered obstacles for collision avoidance between multi mobile robots are static, dynamic, or both of them at the same time. Using the fuzzy rule based structure, distance and angle from a robot to obstacles are described as fuzzy linguistic values and steering angle for the robot are updated from the collision environments. As a result, the multi-mobile robot can modify a global path from a robot itself to its own target. In addition, avoiding collision with static or dynamic obstacles for the robot system can be achieved. Simulation based experimental results are given to show usefulness of this method.

Development of Comfort Feeling Structure in Indoor Environments Using Hybrid Neuralnetworks (하이브리드 신경망을 이용한 실내(室內) 쾌적감성(快適感性)모형 개발)

  • Jeon, Yong-Ung;Jo, Am
    • Journal of the Ergonomics Society of Korea
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    • v.20 no.2
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    • pp.29-46
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    • 2001
  • This study is about the modeling of comfort feeling structure in indoor environments. To represent the degree of practical comfort feeling level in an environment, we measured elements of human sense and resultant elements of comfort feeling such as coziness, refreshment, and freshness with physical values(temperature, illumination, noise. etc.). The relationships of elements of human sense and elements of comfort feeling were formulated as a fuzzy model. And a hybrid-neural network with three layers were designed where obtained from fuzzy membership function values of the elements of human sense were used as inputs, and given as fuzzy membership function values of resultant elements of comfort feeling were used as outputs. Both kinds of fuzzy membership function values were obtained from physical values. The network was trained by measured data set. The proposed hybrid-neural network were tested and proposed a more realistic model of comfort feeling structure in indoor environments.

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Fuzzy Variable Structure Control of Wheel-Driven Inverted Pendulum (바퀴구동 도립진자에 대한 퍼지 가변구조제어)

  • Yoo Byung-Kook
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.4
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    • pp.301-307
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    • 2004
  • This paper suggests a fuzzy variable structure control scheme for Takagi-Sugeno(T-S) fuzzy model and presents the attitude control of the wheel-driven inverted pendulum(WDIP) based on the proposed control algorithm. The proposed controller is designed based on the T-S fuzzy modeling of nonlinear system and the unification of gain matrices in linear subsystems that constitute the overall fuzzy model. The uncertainties generated in the gain matrix unifying procedure can be interpreted as the input disturbances of the conventional variable structure control. These unifying disturbances can be resolved by using the robustness property of the conventional variable structure system. Design example for wheel-driven inverted pendulum demonstrates the utility and validity of the proposed control scheme.

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