• Title/Summary/Keyword: Fuzzy Relation

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An efficient Decision-Making using the extended Fuzzy AHP Method(EFAM) (확장된 Fuzzy AHP를 이용한 효율적인 의사결정)

  • Ryu, Kyung-Hyun;Pi, Su-Young
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.6
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    • pp.828-833
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    • 2009
  • WWW which is an applicable massive set of document on the Web is a thesaurus of various information for users. However, Search engines spend a lot of time to retrieve necessary information and to filter out unnecessary information for user. In this paper, we propose the EFAM(the Extended Fuzzy AHP Method) model to manage the Web resource efficiently, and to make a decision in the problem of specific domain definitely. The EFAM model is concerned with the emotion analysis based on the domain corpus information, and it composed with systematic common concept grids by the knowledge of multiple experts. Therefore, The proposed the EFAM model can extract the documents by considering on the emotion criteria in the semantic context that is extracted concept from the corpus of specific domain and confirms that our model provides more efficient decision-making through an experiment than the conventional methods such as AHP and Fuzzy AHP which describe as a hierarchical structure elements about decision-making based on the alternatives, evaluation criteria, subjective attribute weight and fuzzy relation between concept and object.

An Algorithm of Short-Term Load Forecasting (단기수요예측 알고리즘)

  • Song Kyung-Bin;Ha Seong-Kwan
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.53 no.10
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    • pp.529-535
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    • 2004
  • Load forecasting is essential in the electricity market for the participants to manage the market efficiently and stably. A wide variety of techniques/algorithms for load forecasting has been reported in many literatures. These techniques are as follows: multiple linear regression, stochastic time series, general exponential smoothing, state space and Kalman filter, knowledge-based expert system approach (fuzzy method and artificial neural network). These techniques have improved the accuracy of the load forecasting. In recent 10 years, many researchers have focused on artificial neural network and fuzzy method for the load forecasting. In this paper, we propose an algorithm of a hybrid load forecasting method using fuzzy linear regression and general exponential smoothing and considering the sensitivities of the temperature. In order to consider the lower load of weekends and Monday than weekdays, fuzzy linear regression method is proposed. The temperature sensitivity is used to improve the accuracy of the load forecasting through the relation of the daily load and temperature. And the normal load of weekdays is easily forecasted by general exponential smoothing method. Test results show that the proposed algorithm improves the accuracy of the load forecasting in 1996.

The Tuning Method on Consequence Membership Function of T-S Type FLC (T-S형 퍼지제어기의 후건부 멤버십함수 동조방법)

  • Choi, Han-Soo;Lee, Kyoung-Woong
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.3
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    • pp.264-268
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    • 2011
  • This paper presents a Takagi-Sugeno (T-S) type Fuzzy Logic Controller (FLC) with only 3 rules. The choice of parameters of FLC is very difficult job on design FLC. Therefore, the choice of appropriate linguistic variable is an important part of the design of fuzzy controller. However, since fuzzy controller is nonlinear, it is difficult to analyze mathematically the affection of the linguistic variable. So this choice is depend on the expert's experience and trial and error method. In this paper, we propose the method to choose the consequence linear equation's parameter of T-S type FLC. The parameters of consequence linear equations of FLC are tuned according to the system error that is the input of FLC. The full equation of T-S type FLC is presented and using this equation, the relation between output and parameters can represented. The parameters are tuned with gradient algorithm. The parameters are changed depending on output. The simulation results demonstrate the usefulness of this T-S type 3 rule fuzzy controller.

An Evaluation Model of Corporate Culture Using Fuzzy System (퍼지시스템을 이용한 기업문화 평가모델)

  • Kim, Chun-Ho;Hwang, Seung-Gook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.2
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    • pp.267-272
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    • 2010
  • This paper suggests an evaluation method through corporate culture's evaluation model considering the relationship and affection between types and elements of corporate culture. 314 data obtained from the members of small and medium enterprises analyzed the relationship by the correlation analysis, and the degree affecting rate the corporate culture types by the regression analysis. Finally, fuzzy system was used to analyze the evaluation model of the corporate culture type. The evaluation model of the corporate culture types in this paper is mixed possibility and necessity sides and showed the usefulness through reviewing the model which has an identification problem of the fuzzy system estimated fuzzy relation matrix for corporate culture types using the model.

Flame Diagnosis Using Neuro-Fuzzy Learning Algorithm (뉴로퍼지학습 알고리듬을 이용한 연소상태진단)

  • Lee, Tae-Yeong;Kim, Seong-Hwan;Lee, Sang-Ryong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.4
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    • pp.587-595
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    • 2002
  • Recent trend changes a criterion for evaluation of humors that environmental problems are raised as a global issue. Burners with higher thermal efficiency and lower oxygen in the exhaust gas, evaluated better. To comply with environmental regulations, burners must satisfy the NO/sub x/ and CO regulation. Consequently, 'good burner'means one whose thermal efficiency is high under the constraint of NO/sub x/ and CO consistency. To make existing burner satisfy recent criterion, it is highly recommended to develop a feedback control scheme whose output is the consistency of NO/sub x/ and CO. This paper describes the development of a real time flame diagnosis technique that evaluate and diagnose the combustion states, such as consistency of components in exhaust gas, stability of flame in the quantitative sense. In this paper, it was proposed on the flame diagnosis technique of burner using Neuro-Fuzzy algorithm. This study focuses on the relation of the color of the flame and the state of combustion. Neuro-Fuzzy loaming algorithm is used in obtaining the fuzzy membership function and rules. Using the constructed inference algorithm, the amount of NO/sub x/ and CO of the combustion gas was successfully inferred.

A Fuzzy Controller for Warp Tension Control in The Weaving Process (퍼지제어기를 이용한 제작공정에서의 경사장력제어)

  • 류도훈;이연정
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.335-339
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    • 2000
  • In the weaving process, tension control of the warp is important. The variation of the warp tension cause irregularities of the weft density and low quality of the woven fabrics. Due to the fact that the warp tension varies in depending on the difference between take-up velocity and let-off velocity, it is necessary to regulate the velocity of let-off in relation to that of take-up for keeping the warp tension. Futhermore, the diameter of warp beam changes in the weaving process. The changing diameter of warp beam cause changing inertia of warp beam and the velocity of the let-off. It makes the control of such a system more complex. In this paper, we propose a fuzzy controller for the warp tension control. From the computer simulation, it was observed that a developed fuzzy controller has a better performance than that of conventional PI controller.

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A Study on the Development of Purchasing Decision Model by Image of Product - A Fuzzy Rule Based Analysis- (퍼지를 이용한 제품 이미지에 따른 구매결정모형에 개발에 관한 연구)

  • Park, Sang-June;Cho, Jai-Rip
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.05a
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    • pp.86-91
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    • 2004
  • As many organizations are searching for ways to compete more effectively in today's market environment. Image of Product is become the most important fact to improve their competition. The objectives of this paper are to provide an overview of PDM(Purchasing Decision Factor) and to discuss how to measure it more efficiently. This study develops a conceptual 'relation model of the purchasing decision factor', which identifies only performance based measurement, and proposes Fuzzy Measuring Method which uses the Fuzzy rule based algorithm to adept survey to date sets.

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Distributed Multimedia Object Management Platform Using Weight and Fuzzy Filtering (가중치와 퍼지 필터링을 이용한 분산 멀티미디어 객체 관리 플랫폼)

  • Lee Chong-Deuk;Jeong Taeg-Won
    • Journal of Digital Contents Society
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    • v.4 no.1
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    • pp.81-90
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    • 2003
  • Multimedia Platform box based on distributed environments have much effect on objects grouping for management of distributed resources. This paper utilizes weight and fuzzy filtering techniques for objects platform in distributed multimedia environments. Weight and Fuzzy filtering techniques perform grouping by references relation of multimedia objects and this paper proposes object dictionary structure.

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LATTICE OF KEYCHAINS

  • MURALI V.
    • Journal of applied mathematics & informatics
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    • v.20 no.1_2
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    • pp.409-420
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    • 2006
  • In this paper we consider the set of all n + 1-tuples of real numbers, not necessarily all distinct, in the decreasing order from the unit interval under the usual ordering of real numbers, always including 1. Such n + 1-tuples inherently arise as the membership values of fuzzy subsets and are called keychains. An natural equivalence relation is introduced on this set and the equivalence classes of keychains are studied here. The number of such keychains is finite and the set of all keychains is a lattice under the coordinate-wise ordering. Thus keychains are subchains of a finite chain of real numbers in the unit interval. We study some of their properties and give some applications to counting fuzzy subsets of finite sets.

A Study on the Automation of Deburring Process Using Vision Sensor (비젼 센서를 이용한 디버링 공정의 자동화에 관한 연구)

  • 신상운;갈축석;강근택;안두성
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1994.10a
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    • pp.553-558
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    • 1994
  • In this paper, we present a new approach for the automation of deburring process. An algorithm for teaching skills of a human expert to a robot manipulator is developed. This approach makes use of TSK fuzzy model that can express a highly nonlinear functional relation with small number of rules. Burr features such as height, width, area, cutting area are extracted from image processing by use of the vision system. Cutting depth, repeative number and normal cutting force are chosen as control signals representing actions of the human expert. It is verified that our processed fuzzy model can accurately express the skills of human experts for the deburring process.

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