• Title/Summary/Keyword: possibility distribution function

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A Bayesian Fuzzy Hypotheses Testing with Loss Function (손실함수에 의한 베이지안 퍼지 가설검정)

  • 강만기;한성일;최규탁
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09b
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    • pp.45-48
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    • 2003
  • We propose some properties of Bayesian fuzzy hypotheses testing by revision for prior possibility distribution and posterior possibility distribution using weighted fuzzy hypotheses H$\sub$0/($\theta$) versus H$_1$($\theta$) on $\theta$ with loss function.

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Relaxation algorithm to solve correspondence problem based on possibility distribution (정합 문제 해결을 위한 가능도 기반의 이완 처리 알고리즘)

  • 한규필;김용석;박영식;송근원;하영호
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.9
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    • pp.109-117
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    • 1997
  • A new relaxation algorithm based on distribution of matched errors and possibility is proposed to solve efficiently correspondence problem. This algorithm can be applied to various method, such as BMA, feature-, and region-based matching methods, by modifying its smoothness function. It consists of two stages which are transformation and iteration process. In transformation stage, the errors obtained by any matching algorithm are transformed to possibility values according to these statistical distribution. Each grade of possility is updated by some constraints which are defined as smoothness, uniqueness, and discontinuity factor in iteration stage. The discontinuity factor is used to reserve discontinuity of disparity. In conventional methods, it is difficult to find proper weights and stop condition, because only two factors, smoothness and uniqueness, have been used. However, in the proposed mthod, the more smoothing is not ocurred because of discontinuity factor. And it is efective to the various image, even if the image has a severe noise and repeating patterns. In addition, it is shown that the convergence rate and the quality of output are improved.

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An Evaluation on the Degrees of Satisfaction of Product with Hierarchical Quality Structure Using Possibility Distribution Function (가능성분포함수를 이용한 계층적 품질구조를 가진 제품의 만족도 평가)

  • 김정만
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.21 no.46
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    • pp.173-180
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    • 1998
  • In conventional probability-based quality evaluation of products with qualitative characteristics, many factors that affect the evaluation are not easily represented quantitatively, because the relation between reliability of human evaluator and each of these factors is not clear. In order to evaluate the quality of product with qualitative characteristics quantitatively, in this paper, the relation is represented as the shape of possibility distribution function of fuzzy set on the interval [0,1]. Furthermore, fuzzy reasoning is used to obtain the estimates of quality characteristics. And, it is supposed that many quality characteristics affected by the above factors are connected with the final characteristic through hierarchical structures. Finally, using the estimates gained from the final evaluation, qualitative characteristics are evaluated by use of concept of pattern recognition.

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A Probabilistic Analysis on Fracture Strength of Ceramics (세라믹스의 파괴강도에 관한 확률론적 해석)

  • 김선진
    • Journal of Ocean Engineering and Technology
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    • v.10 no.2
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    • pp.61-68
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    • 1996
  • Weibull distribution function is applied very successfully to the strength of brittle materials such as ceramics and the weakest link model is applied to explain the ovents. This paper deals with the effect of specimen size on the strength of ceramics. The values of tensile strength were calculated by the Monte-Calro simuation. The tensile strength obtained was plotted on Weibull probabillity papers and represented by the 3-parameter Weibull distribution. The strength distribution function was compared with the theoretical weibull distribution. As a result, it was found that the Weibull shape parameter was changed due to the size and there was a possibility of a false indication as if the weakest link model holds good. We should be very careful when we apply the Weibull statistics to estimate the strength of products.

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A Note on Possibilistic Correlation

  • Hong, Dug-Hun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.1
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    • pp.1-3
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    • 2009
  • Recently, Carlsson, Full\acute{e}$r and Majlender [1] presented the concept of possibilitic correlation representing an average degree of interaction between marginal distribution of a joint possibility distribution as compared to their respective dispersions. They also formulated the weak and strong forms of the possibilistic Cauchy-Schwarz inequality. In this paper, we define a new probability measure. Then the weak and strong forms of the Cauchy-Schwarz inequality are immediate consequence of probabilistic Cauchy-Schwarz inequality with respect to the new probability measure.

A Lane Departure Warning Algorithm Based on an Edge Distribution Function (에지분포함수 기반의 차선이탈경보 알고리즘)

  • 이준웅;이성웅
    • Transactions of the Korean Society of Automotive Engineers
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    • v.9 no.3
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    • pp.143-154
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    • 2001
  • An algorithm for estimating the lane departure of a vehicle is derived and implemented based on an EDF(edge distribution function) obtained from gray-level images taken by a CCD camera mounted on a vehicle. As the function of edge direction, the EDF is aimed to show the distribution of edge direction and to estimate the possibility of lane departure with respect to its symmetric axis and local mamma. The EDF plays important roles: 1) It reduces noisy effects caused by dynamic road scene. 2) It makes possible lane identification without camera modeling. 3) It also leads LDW(lane departure warning) problem to a mathematical approach. When the situations of lane departure such that the vehicle approaches to lane marks or runs in the vicinity of the lane marks are occurred, the orientation of lane marks in images is changed, and then the situations are immediately reflected to the EDF. Accordingly, the lane departure is estimated by studying the shape of the EDF. The proposed EDF-based algorithm enhanced the adaptability to cope with the random and dynamic road environments, and eventually led to the reliable LDW system.

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Evaluation of Overtopping Risks of Levee by using Reliability Analysis (신뢰성 해석에 의한 제방의 월류 위험도 산정)

  • Lee, Cheol-Eung;Park, Dong-Heon;Shim, Jae-Wook
    • Journal of Industrial Technology
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    • v.29 no.A
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    • pp.101-110
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    • 2009
  • Due to frequent occurrence of a localized torrential downpour caused by global warming and change of outflow tendency caused by rapid urbanization and industrialization, risk analysis must be carried out in levee design with uncertainty. In this study, reliability analysis was introduced to quantitatively evaluate the overtopping risk of levee by the uncertainty. First of all, breaking function was established as a function of flood stage and height of levee. All variables of breaking function were considered as random variables following any distribution functions, and the risk was defined as the possibility that the flood stage is formed higher than height of levee. The risk evaluation model was developed with AFDA (Approximate Full Distribution Approach). The flood stage computed by 2-D numerical model FESWMS-2DH was used as input data for the model of levee risk evaluation. Risk for levee submergence were quantitatively presented for levee of Wol-Song-Cheon.

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An Alternative Perspective to Resolve Modelling Uncertainty in Reliability Analysis for D/t Limitation Models of CFST (CFST의 D/t 제한모델들에 대한 신뢰성해석에서 모델링불확실성을 해결하는 선택적 방법)

  • Han, Taek Hee;Kim, Jung Joong
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.28 no.4
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    • pp.409-415
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    • 2015
  • For the design of Concrete-Filled Steel Tube(CFST) columns, the outside diameter D to the steel tube thickness t ratio(D/t ratio) is limited to prevent the local buckling of steel tubes. Each design code proposes the respective model to compute the maximum D/t ratio using the yield strength of steel $f_y$ or $f_y$ and the elastic modulus of steel E. Considering the uncertainty in $f_y$ and E, the reliability index ${beta}$ for the local buckling of a CFST section can be calculated by formulating the limit state function including the maximum D/t models. The resulted ${beta}$ depends on the maximum D/t model used for the reliability analysis. This variability in reliability analysis is due to ambiguity in choosing computational models and it is called as "modelling uncertainty." This uncertainty can be considered as "non-specificity" of an epistemic uncertainty and modelled by constructing possibility distribution functions. In this study, three different computation models for the maximum D/t ratio are used to conduct reliability analyses for the local buckling of a CFST section and the reliability index ${beta}$ will be computed respectively. The "non-specific ${beta}s$" will be modelled by possibility distribution function and a metric, degree of confirmation, is measured from the possibility distribution function. It is shown that the degree of confirmation increases when ${beta}$ decreases. Conclusively, a new set of reliability indices associated with a degree of confirmation is determined and it is allowed to decide reliability index for the local buckling of a CFST section with an acceptable confirmation level.

New Inference for a Multiclass Gaussian Process Classification Model using a Variational Bayesian EM Algorithm and Laplace Approximation

  • Cho, Wanhyun;Kim, Sangkyoon;Park, Soonyoung
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.4
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    • pp.202-208
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    • 2015
  • In this study, we propose a new inference algorithm for a multiclass Gaussian process classification model using a variational EM framework and the Laplace approximation (LA) technique. This is performed in two steps, called expectation and maximization. First, in the expectation step (E-step), using Bayes' theorem and the LA technique, we derive the approximate posterior distribution of the latent function, indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. In the maximization step, we compute the maximum likelihood estimators for hyper-parameters of a covariance matrix necessary to define the prior distribution of the latent function by using the posterior distribution derived in the E-step. These steps iteratively repeat until a convergence condition is satisfied. Moreover, we conducted the experiments by using synthetic data and Iris data in order to verify the performance of the proposed algorithm. Experimental results reveal that the proposed algorithm shows good performance on these datasets.