• 제목/요약/키워드: data perturbation

검색결과 221건 처리시간 0.027초

Some Results on the Log-linear Regression Diagnostics

  • Yang, Mi-Young;Choi, Ji-Min;Kim, Choong-Rak
    • Communications for Statistical Applications and Methods
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    • 제14권2호
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    • pp.401-411
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    • 2007
  • In this paper we propose an influence measure for detecting potentially influential observations using the infinitesimal perturbation and the local influence in the log-linear regression model. Also, we propose a goodness-of-fit measure for variable selection. A real data set are used for illustration.

SOLUTIONS OF QUASILINEAR WAVE EQUATION WITH STRONG AND NONLINEAR VISCOSITY

  • Hwang, Jin-Soo;Nakagiri, Shin-Ichi;Tanabe, Hiroki
    • 대한수학회지
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    • 제48권4호
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    • pp.867-885
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    • 2011
  • We study a class of quasilinear wave equations with strong and nonlinear viscosity. By using the perturbation method for semilinear parabolic equations, we have established the fundamental results on existence, uniqueness and continuous dependence on data of weak solutions.

Topological Analysis of Large Scale Structure Using the Final BOSS Sample

  • 최윤영;김주한
    • 천문학회보
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    • 제39권2호
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    • pp.43.2-43.2
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    • 2014
  • We present the three-dimensional genus topology of large-scale structure using the CMASS sample of the Final SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS) data. To estimate the uncertainties in the measured genus, we very carefully construct mock CMASS surveys along the past light cone from the Horizon Run 3. We find that the shape of the observed genus curve agrees very well with the prediction of perturbation theory and with the mean topology of the mock surveys. However, comparison with simulations show that the observed genus curve slightly deviates from the theoretical Gaussian expectation. From the deviation, we further quantify the primordial non-Gaussian contribution.

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A REFINED THEOREM CONCERNING THE CONDITIONING OF SEMIDEFINITE PROGRAMS

  • Argyros, Ioannis K.
    • Journal of applied mathematics & informatics
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    • 제24권1_2호
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    • pp.305-312
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    • 2007
  • Using a weaker version of the Newton-Kantorovich theorem [6] given by us in [3], we show how to refine the results given in [8] dealing with the analyzing of the effect of small perturbations in problem data on the solution. The new results are obtained under weaker hypotheses and the same computational cost as in [8].

Improving Bagging Predictors

  • Kim, Hyun-Joong;Chung, Dong-Jun
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2005년도 추계 학술발표회 논문집
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    • pp.141-146
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    • 2005
  • Ensemble method has been known as one of the most powerful classification tools that can improve prediction accuracy. Ensemble method also has been understood as ‘perturb and combine’ strategy. Many studies have tried to develop ensemble methods by improving perturbation. In this paper, we propose two new ensemble methods that improve combining, based on the idea of pattern matching. In the experiment with simulation data and with real dataset, the proposed ensemble methods peformed better than bagging. The proposed ensemble methods give the most accurate prediction when the pruned tree was used as the base learner.

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FBG를 이용한 Optical Finer 구현 (Implementation of the Optical Filter Using FBG)

  • 이종윤;신희성;손용환;이창원;정진호
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 하계종합학술대회 논문집(1)
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    • pp.223-226
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    • 2002
  • In this paper, we propose the FBG design using coupled mode theory based on perturbation theory. FBG can be used to extract the specific wavelength channel from the transmission ]me when many wavelengths are coupled in a multiwavelength transmission line. To analyze output characteristics of FBG and get optimum design data, we simulate through computer and verify by experiment. From the results obtained by simulation and experimentation, the proposed FBG fits for DWDM(Dense WBM) system because of the tunning narrow linewidth.

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신경망기법을 이용한 구조물 접합부의 손상평가 (Structural Joint damage Estimation by Neural Networks Incorporating Advanced Techniques)

  • 이진학
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 1999년도 춘계 학술발표회 논문집 Proceedings of EESK Conference-Spring
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    • pp.300-307
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    • 1999
  • 신경망기법을 이용한 구조물접합부의 손상평가기법을 제안하였다. 신경망기법의 성능을 개선하기 위하여 노이즈첨가학습을 수행하였으며 효과적인 손상평가를 위하여 부분구조추정법 및 data perturbation scheme을 도입하였다. 10층 프레임구조물에 대한 수치해석과 2층 프레임구조물에 대한 실험연구를 통하여 제안기법을 검증하였다 계측지점이 부분구조로 제한되고 계측자료가 노이즈를 포함하는 경우에는 제안기법이 효과적으로 적용될수 있음을 알 수 있었으며 실험을 통하여 실제 구조물에 대한 제안기법의 적용성을 평가힐 수 있었다.

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OBSERVATIONAL STATUS OF THE TEXTURE LARGE-SCALE STRUCTURE FORMATION MODEL

  • UMEDA HIDEYUKI;FREESE KATHERINE
    • 천문학회지
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    • 제29권spc1호
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    • pp.23-24
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    • 1996
  • We reexamined CDM texture large-scale structure (LSS) formation model. We confirmed that texture model is consistent with 4-year COBE data both in an open and a critical matter density (${\Omega}_0$ = 1) universes, and then obtained normalization for density perturbation power spectrum. We next compare the power spectrum with LSS observation data. Contrary to the previous literature, we found that texture model matches with these data in an open universe no better than in an ${\Omega}_0$ = 1 universe. We also found that the model is more likely to fit these data in a cosmological constant dominated ($\Lambda-$) universe.

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K-means 알고리즘 기반 클러스터링 인덱스 비교 연구 (A Performance Comparison of Cluster Validity Indices based on K-means Algorithm)

  • 심요성;정지원;최인찬
    • Asia pacific journal of information systems
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    • 제16권1호
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    • pp.127-144
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    • 2006
  • The K-means algorithm is widely used at the initial stage of data analysis in data mining process, partly because of its low time complexity and the simplicity of practical implementation. Cluster validity indices are used along with the algorithm in order to determine the number of clusters as well as the clustering results of datasets. In this paper, we present a performance comparison of sixteen indices, which are selected from forty indices in literature, while considering their applicability to nonhierarchical clustering algorithms. Data sets used in the experiment are generated based on multivariate normal distribution. In particular, four error types including standardization, outlier generation, error perturbation, and noise dimension addition are considered in the comparison. Through the experiment the effects of varying number of points, attributes, and clusters on the performance are analyzed. The result of the simulation experiment shows that Calinski and Harabasz index performs the best through the all datasets and that Davis and Bouldin index becomes a strong competitor as the number of points increases in dataset.

NCURO DATA RETRIEVAL ALGORITHM IN FORMOSAT-3 GPS RADIO OCCULTATION OBSERVATION OF GRAVITY WAVE ACTIVITY

  • Yeh, Wen-Hao;Chiu, Tsen-Chieh;Liou, Yuei-An;Yan, Shian-Kun;Huang, Cheng-Yung
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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    • pp.192-195
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    • 2008
  • Radio occultation (RO) has been used in the planetary science since Microlab-1 was launched in 1995. With the RO technique, the profiles of atmosphere and the global atmospheric data can be obtained. In 2006, Taiwan launched six low Earth orbit (LEO) satellites as the RO constellation mission, known as FORMOSAT-3. In order to retrieve the RO data from original data, a retrieval algorithm, NCURO, is developed. The input of NCURO algorithm is mainly the excess phase of GPS signal, and the output is the dry pressure and dry temperature. Using temperature profiles retrieved by NCURO algorithm, temperature perturbation and potential energy of gravity wave have been evaluated. In this paper, the retrieval algorithm and the global distribution of energy of gravity waves are described and demonstrated.

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