• 제목/요약/키워드: Fuzzy mathematics method

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SAOR METHOD FOR FUZZY LINEAR SYSTEM

  • Miao, Shu-Xin;Zheng, Bing
    • Journal of applied mathematics & informatics
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    • 제26권5_6호
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    • pp.839-850
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    • 2008
  • In this paper, the symmetric accelerated overrelaxation (SAOR) method for solving $n{\times}n$ fuzzy linear system is discussed, then the convergence theorems in the special cases where matrix S in augmented system SX = Y is H-matrices or consistently ordered matrices and or symmetric positive definite matrices are also given out. Numerical examples are presented to illustrate the theory.

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A NUMERICAL METHOD OF FUZZY DIFFERENTIAL EQUATIONS

  • Jun, Younbae
    • 한국수학교육학회지시리즈B:순수및응용수학
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    • 제24권3호
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    • pp.147-153
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    • 2017
  • In this paper, we propose a numerical method to solve fuzzy differential equations. Numerical experiments show that when the step size is small, the new method has significantly good approximate solutions of fuzzy differential equation. Graphical representation of fuzzy solutions in three-dimension is also provided as a reference of visual convergence of the solution sequence.

Support Vector Machine Based on Type-2 Fuzzy Training Samples

  • Ha, Ming-Hu;Huang, Jia-Ying;Yang, Yang;Wang, Chao
    • Industrial Engineering and Management Systems
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    • 제11권1호
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    • pp.26-29
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    • 2012
  • In order to deal with the classification problems of type-2 fuzzy training samples on generalized credibility space. Firstly the type-2 fuzzy training samples are reduced to ordinary fuzzy samples by the mean reduction method. Secondly the definition of strong fuzzy linear separable data for type-2 fuzzy samples on generalized credibility space is introduced. Further, by utilizing fuzzy chance-constrained programming and classic support vector machine, a support vector machine based on type-2 fuzzy training samples and established on generalized credibility space is given. An example shows the efficiency of the support vector machine.

WEIGHTED POSSIBILISTIC VARIANCE AND MOMENTS OF FUZZY NUMBERS

  • Pasha, E.;Asady, B.;Saeidifar, A.
    • Journal of applied mathematics & informatics
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    • 제26권5_6호
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    • pp.1169-1183
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    • 2008
  • In this paper, a method to find the weighted possibilistic variance and moments about the mean value of fuzzy numbers via applying a difuzzification using minimizer of the weighted distance between two fuzzy numbers is introduced. In this way, we obtain the nearest weighted point with respect to a fuzzy number, this main result is a new and interesting alternative justification to define of weighted mean of a fuzzy number. Considering this point and the weighted distance quantity, we introduce the weighted possibilistic mean (WPM) value and the weighted possibilistic variance(WPV) of fuzzy numbers. This paper shows that WPM is the nearest weighted point to fuzzy number and the WPV of fuzzy number is preserved more properties of variance in probability theory so that it can simply introduce the possibilistic moments about the mean of fuzzy numbers without problem. The moments of fuzzy numbers play an important role to estimate of parameters, skewness, kurtosis in many of fuzzy times series models.

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An Improved Multilevel Fuzzy Comprehensive Evaluation to Analyse on Engineering Project Risk

  • LI, Xin;LI, Mufeng;HAN, Xia
    • 융합경영연구
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    • 제10권5호
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    • pp.1-6
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    • 2022
  • Purpose: To overcome the question that depends too much on expert's subjective judgment in traditional risk identification, this paper structure the multilevel generalized fuzzy comprehensive evaluation mathematics model of the risk identification of project, to research the risk identification of the project. Research design, data and methodology: This paper constructs the multilevel generalized fuzzy comprehensive evaluation mathematics model. Through iterative algorithm of AHP analysis, make sure the important degree of the sub project in risk analysis, then combine expert's subjective judgment with objective quantitative analysis, and distinguish the risk through identification models. Meanwhile, the concrete method of multilevel generalized fuzzy comprehensive evaluation is probed. Using the index weights to analyse project risks is discussed in detail. Results: The improved fuzzy comprehensive evaluation algorithm is proposed in the paper, at first the method of fuzzy sets core is used to optimize the fuzzy relation matrix. It improves the capability of the algorithm. Then, the method of entropy weight is used to establish weight vectors. This makes the computation process fair and open. And thereby, the uncertainty of the evaluation result brought by the subjectivity can be avoided effectively and the evaluation result becomes more objective and more reasonable. Conclusions: In this paper, we use an improved fuzzy comprehensive evaluation method to evaluate a railroad engineering project risk. It can give a more reliable result for a reference of decision making.

평가부분에서 지식공간과 퍼지이론의 활용 방안에 관한 연구 (The Study of Applications of Knowledge Space and Fuzzy Theory from the Perspective of Evaluation)

  • 박달원;장이채;김태균;정인철
    • 한국학교수학회논문집
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    • 제6권1호
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    • pp.27-43
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    • 2003
  • 본 논문은 자데교수에 의해 소개된 퍼지집합을 정의하면서 시작된 퍼지이론과 도이거넌과 팔마건에 의해 발전된 지식공간의 수학교육의 교수학습에 효과적으로 적용될 수 있는 모색하고자 하는 의도로 새로운 이론을 소개한다. 특히, 위 두 이론은 평가부분에서 현재의 평가방법이 해결할 수 없는 부분을 접근하여 수학 학습 평가의 새로운 장을 열 것으로 기대한다.

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ON THEIL'S METHOD IN FUZZY LINEAR REGRESSION MODELS

  • Choi, Seung Hoe;Jung, Hye-Young;Lee, Woo-Joo;Yoon, Jin Hee
    • 대한수학회논문집
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    • 제31권1호
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    • pp.185-198
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    • 2016
  • Regression analysis is an analyzing method of regression model to explain the statistical relationship between explanatory variable and response variables. This paper propose a fuzzy regression analysis applying Theils method which is not sensitive to outliers. This method use medians of rate of increment based on randomly chosen pairs of each components of ${\alpha}$-level sets of fuzzy data in order to estimate the coefficients of fuzzy regression model. An example and two simulation results are given to show fuzzy Theils estimator is more robust than the fuzzy least squares estimator.

FUZZY REGRESSION MODEL WITH MONOTONIC RESPONSE FUNCTION

  • Choi, Seung Hoe;Jung, Hye-Young;Lee, Woo-Joo;Yoon, Jin Hee
    • 대한수학회논문집
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    • 제33권3호
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    • pp.973-983
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    • 2018
  • Fuzzy linear regression model has been widely studied with many successful applications but there have been only a few studies on the fuzzy regression model with monotonic response function as a generalization of the linear response function. In this paper, we propose the fuzzy regression model with the monotonic response function and the algorithm to construct the proposed model by using ${\alpha}-level$ set of fuzzy number and the resolution identity theorem. To estimate parameters of the proposed model, the least squares (LS) method and the least absolute deviation (LAD) method have been used in this paper. In addition, to evaluate the performance of the proposed model, two performance measures of goodness of fit are introduced. The numerical examples indicate that the fuzzy regression model with the monotonic response function is preferable to the fuzzy linear regression model when the fuzzy data represent the non-linear pattern.

MULTI-OBJECTIVES FUZZY MODELS FOR DESIGNING 3D TRAJECTORY IN HORIZONTAL WELLS

  • Qian, Weiyi;Feng, Enmin
    • Journal of applied mathematics & informatics
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    • 제15권1_2호
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    • pp.265-275
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    • 2004
  • In this paper, multi-objective models for designing 3D trajectory of horizontal wells are developed in a fuzzy environment. Here, the objectives of minimizing the length of the trajectory and the error of entry target point are fuzzy in nature. Some parameters, such as initial value, end value, lower bound and upper bound of the curvature radius, tool-face angle and the arc length of each curve section, are also assumed to be vague and imprecise. The impreciseness in the above objectives have been expressed by fuzzy linear membership functions and that in the above parameters by triangular fuzzy numbers. Models have been solved by the fuzzy non-linear programming method based on Zimmermann [1] and Lee and Li [2]. Models are applied to practical design of the horizontal wells. Numerical results illustrate the accuracy and efficiency of the fuzzy models.

FUZZY TOPOLOGICAL ORDERED SPACES

  • In, Byung-Sik
    • Journal of applied mathematics & informatics
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    • 제10권1_2호
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    • pp.361-370
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    • 2002
  • We are to present some properties of binary relations on fuzzy topological spares by means of categorical method. The concept of fuzzy topological ordered spaces was introduced by Katsaras[8]. In this paper we study some special categories, i.e, FTQOS, FTPOS, LSCQ, USCQ, SCQ, CQ, NQO, CRQO, associated with fuzzy topological spaces.