• 제목/요약/키워드: geometric mean model

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Testing Outliers in Nonlinear Regression

  • Kahng, Myung-Wook
    • Journal of the Korean Statistical Society
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    • 제24권2호
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    • pp.419-437
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    • 1995
  • Given the specific mean shift outlier model, several standard approaches to obtaining test statistic for outliers are discussed. Each of these is developed in detail for the nonlinear regression model, and each leads to an equivalent distribution. The geometric interpretations of the statistics and accuracy of linear approximation are also presented.

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A Score test for Detection of Outliers in Nonlinear Regression

  • Kahng, Myung-Wook
    • Journal of the Korean Statistical Society
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    • 제22권2호
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    • pp.201-208
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    • 1993
  • Given the specific mean shift outlier model, the score test for multiple outliers in nonlinear regression is discussed as an alternative to the likelihood ratio test. The geometric interpretation of the score statistic is also presented.

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일반화 기하분포를 이용한 ARL의 수정에 관한 연구 (A Study on the Alternative ARL Using Generalized Geometric Distribution)

  • 문명상
    • 품질경영학회지
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    • 제27권4호
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    • pp.143-152
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    • 1999
  • In Shewhart control chart, the average run length(ARL) is calculated using the mean of a conventional geometric distribution(CGD) assuming a sequence of identical and independent Bernoulli trials. In this, the success probability of CGB is the probability that any point exceeds the control limits. When the process is in-control state, there is no problem in the above assumption since the probability that any point exceeds the control limits does not change if the in-control state continues. However, if the out-of-control state begins and continues during the process, the probability of exceeding the control limits may take two forms. First, once the out-of-control state begins with exceeding probability p, it continues with the same exceeding probability p. Second, after the out-of-control state begins, the exceeding probabilities may very according to some pattern. In the first case, ARL is the mean of CGD with success probability p as usual. But in the second case, the assumption of a sequence of identical and independent Bernoulli trials is invalid and we can not use the mean of CGD as ARL. This paper concentrate on that point. By adopting one generalized binomial distribution(GBD) model that allows correlated Bernoulli trials, generalized geometric distribution(GGD) is defined and its mean is derived to find an alternative ARL when the process is in out-of-control state and the exceeding probabilities take the second form mentioned in the above. Small-scale simulation is performed to show how an alternative ARL works.

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토크 컨버터의 형상 분석 (Geometrical Analysis of a Torque Converter)

  • 임원석
    • 한국자동차공학회논문집
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    • 제5권5호
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    • pp.197-212
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    • 1997
  • The performance of a torque converter can be expressed by the performance parameters such as flow radius and flow angle, on the mean flow path. The geometric analysis of the torque converter is required to determine these parameters for the modeling of the torque converter. In general, the blade shape is depicted by three dimensional data at the mid-surface of blade or those of the pressure and suction side. To generate three dimensional model of the blade using the data mentioned above, a consistent data format and a shape generation algorithm are required. This paper presents a useful consistent data format of the blades and an algorithm for the geometrical shape generation. By the geometric analysis program to which the shape generation algorithm is embedded, the variation of blade angles in rotating element analyzed. Then finally, the analyzed results of geometric profile of a blade are compared with those of the blade design principle, so called forced vortex theorem.

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Three extended geometric process models for modeling reliability deterioration and improvement

  • Jiang, R.
    • International Journal of Reliability and Applications
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    • 제12권1호
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    • pp.49-60
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    • 2011
  • The geometric process (GP) has been widely used for modeling failure and repair time sequences of repairable systems. The GP is mathematically tractable but restrictive in reliability applications since it actually assumes that the mean function of inter-failure times sequence asymptotically decreases to zero; and the mean function of successive repair times sequence asymptotically increases to infinity. This is generally unrealistic from an engineering perspective. This paper presents three extended GP models for modeling reliability deterioration and improvement (or growth) process. The extensions maintain the advantage of mathematical tractability of GP model. Their usefulness and appropriateness are illustrated with three real-world examples.

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Utilization of deep learning-based metamodel for probabilistic seismic damage analysis of railway bridges considering the geometric variation

  • Xi Song;Chunhee Cho;Joonam Park
    • Earthquakes and Structures
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    • 제25권6호
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    • pp.469-479
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    • 2023
  • A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.

SMAT 알고리즘을 이용한 위상학적 모델 추출 방법 (The Research on Extraction of Topology Model Using Straight Medial Axis Transformation Algorithm)

  • 박소영;이지영
    • Spatial Information Research
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    • 제20권2호
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    • pp.117-127
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    • 2012
  • 본 연구는 실내 GIS 모델을 구축하기 위한 위상학적 모델이 객체의 기하학적 특징을 반영할 필요성에 의해, 기하적 정보를 갖는 위상학적 모델인 기하 네트워크 모델을 자동 구축하는 알고리즘을 개발하는 것을 목적으로 한다. GNM의 요소 중 기하 정보를 갖는 요소를 자동 추출하기 위한 중심 알고리즘으로서 직선 중심축 추출 알고리즘을 개발하였다. 개발된 SMAT 알고리즘은 기존의 S-MAT 알고리즘을 활용하여 일반화되었고, 해당되는 객체의 범위를 단순 폴리곤에서 내부 폐색 구역을 갖는 폴리곤으로 확장하였다. 자동 구축된 GNM은 타 시스템에서의 활용 및 용이한 접근을 위해 최종적으로 .csv 파일로 출력된다. GNM 자동 추출 알고리즘은 최단 경로 탐색, 위급 상황 발생 시 대피로 안내, 상황에 따른 차별적 분석 등 다양한 경우에 효율적으로 활용될 수 있다.

Compatibility를 이용한 다수 전문가의 가중치 종합화에 관한 연구 (A Study on the Aggregation of Multi-Experts Priorities Using Compatibility in the AHP)

  • 조성훈;김태성;이영찬
    • 한국경영과학회지
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    • 제23권4호
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    • pp.131-140
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    • 1998
  • The objective of this study is to propose a new procedure to synthesize the multi-experts priorities in AHP. If multi-experts with different expertise are involved in a AHP decision, we need some way to aggregate their opinions. AHP model used to do numerical aggregation by taking only the geometric mean or the weighting geometric mean in past. To aggregate the multi-experts priorities, In this paper. we suggest a way which Decision Maker can exclude outlier matrix from group using the concept of the Compatibility and we Introduce Delphi method to use Compatibility in AHP. A numerical example is shown to illustrate the procedure.

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그래프 모형을 이용한 지수분포 모수들의 기하평균 비교에 관한 연구 (On Multiple Comparison of Geometric Means of Exponential Parameters via Graphical Model)

  • 김대황;김혜중
    • 응용통계연구
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    • 제19권3호
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    • pp.447-460
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    • 2006
  • 본 연구에서는 확률모형의 모수로부터 얻어지는 여러 형태의 함수간의 크기를 다중 비교 하는 방법을 제안하고자 한다. 이 방법은 비교대상인 모수 함수 간의 선호확률을 베이지안 방법으로 추정하고, 이들로부터 얻어지는 선호행렬을 이용한 새로운 다중비교법이다. 이러한 방법의 제안에 필요한 이론과 비교기준을 고안하였으며, 응용 예로 제안된 방법을 s의 독립인 지수분포 모수의 기하평균 크기 비교에 적용하였다.

Vignetting Dimensional Geometric Models and a Downhill Simplex Search

  • Kim, Hyung Tae;Lee, Duk Yeon;Choi, Dongwoon;Kang, Jaehyeon;Lee, Dong-Wook
    • Current Optics and Photonics
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    • 제6권2호
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    • pp.161-170
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    • 2022
  • Three-dimensional (3D) geometric models are introduced to correct vignetting, and a downhill simplex search is applied to determine the coefficients of a 3D model used in digital microscopy. Vignetting is nonuniform illuminance with a geometric regularity on a two-dimensional (2D) image plane, which allows the illuminance distribution to be estimated using 3D models. The 3D models are defined using generalized polynomials and arbitrary coefficients. Because the 3D models are nonlinear, their coefficients are determined using a simplex search. The cost function of the simplex search is defined to minimize the error between the 3D model and the reference image of a standard white board. The conventional and proposed methods for correcting the vignetting are used in experiments on four inspection systems based on machine vision and microscopy. The methods are investigated using various performance indices, including the coefficient of determination, the mean absolute error, and the uniformity after correction. The proposed method is intuitive and shows performance similar to the conventional approach, using a smaller number of coefficients.