• 제목/요약/키워드: Gaussian modeling

검색결과 264건 처리시간 0.021초

Analyzing nuclear reactor simulation data and uncertainty with the group method of data handling

  • Radaideh, Majdi I.;Kozlowski, Tomasz
    • Nuclear Engineering and Technology
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    • 제52권2호
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    • pp.287-295
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    • 2020
  • Group method of data handling (GMDH) is considered one of the earliest deep learning methods. Deep learning gained additional interest in today's applications due to its capability to handle complex and high dimensional problems. In this study, multi-layer GMDH networks are used to perform uncertainty quantification (UQ) and sensitivity analysis (SA) of nuclear reactor simulations. GMDH is utilized as a surrogate/metamodel to replace high fidelity computer models with cheap-to-evaluate surrogate models, which facilitate UQ and SA tasks (e.g. variance decomposition, uncertainty propagation, etc.). GMDH performance is validated through two UQ applications in reactor simulations: (1) low dimensional input space (two-phase flow in a reactor channel), and (2) high dimensional space (8-group homogenized cross-sections). In both applications, GMDH networks show very good performance with small mean absolute and squared errors as well as high accuracy in capturing the target variance. GMDH is utilized afterward to perform UQ tasks such as variance decomposition through Sobol indices, and GMDH-based uncertainty propagation with large number of samples. GMDH performance is also compared to other surrogates including Gaussian processes and polynomial chaos expansions. The comparison shows that GMDH has competitive performance with the other methods for the low dimensional problem, and reliable performance for the high dimensional problem.

Study on the Dynamic Model and Simulation of a Flexible Mechanical Arm Considering its Random Parameters

  • He Bai-Yan;Wang Shu-Xin
    • Journal of Mechanical Science and Technology
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    • 제19권spc1호
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    • pp.265-271
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    • 2005
  • Randomness exists in engineering. Tolerance, assemble-error, environment temperature and wear make the parameters of a mechanical system uncertain. So the behavior or response of the mechanical system is uncertain. In this paper, the uncertain parameters are treated as random variables. So if the probability distribution of a random parameter is known, the simulation of mechanical multibody dynamics can be made by Monte-Carlo method. Thus multibody dynamics simulation results can be obtained in statistics. A new concept called functional reliability is put forward in this paper, which can be defined as the probability of the dynamic parameters(such as position, orientation, velocity, acceleration etc.) of the key parts of a mechanical multibody system belong to their tolerance values. A flexible mechanical arm with random parameters is studied in this paper. The length, width, thickness and density of the flexible arm are treated as random variables and Gaussian distribution is used with given mean and variance. Computer code is developed based on the dynamic model and Monte-Carlo method to simulate the dynamic behavior of the flexible arm. At the same time the end effector's locating reliability is calculated with circular tolerance area. The theory and method presented in this paper are applicable on the dynamics modeling of general multibody systems.

Removing Out - Of - Distribution Samples on Classification Task

  • Dang, Thanh-Vu;Vo, Hoang-Trong;Yu, Gwang-Hyun;Lee, Ju-Hwan;Nguyen, Huy-Toan;Kim, Jin-Young
    • 스마트미디어저널
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    • 제9권3호
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    • pp.80-89
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    • 2020
  • Out - of - distribution (OOD) samples are frequently encountered when deploying a classification model in plenty of real-world machine learning-based applications. Those samples are normally sampling far away from the training distribution, but many classifiers still assign them high reliability to belong to one of the training categories. In this study, we address the problem of removing OOD examples by estimating marginal density estimation using variational autoencoder (VAE). We also investigate other proper methods, such as temperature scaling, Gaussian discrimination analysis, and label smoothing. We use Chonnam National University (CNU) weeds dataset as the in - distribution dataset and CIFAR-10, CalTeach as the OOD datasets. Quantitative results show that the proposed framework can reject the OOD test samples with a suitable threshold.

지하수위 분포 모델링을 위한 UNIVERSAL KRIGING의 응용 2. 제한적 최대 우도법 (Application of universal kriging for modeling a groundwater level distribution 2. Restricted maximum likelihood method)

  • 정상용
    • 지질공학
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    • 제3권1호
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    • pp.51-61
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    • 1993
  • 비정상 현상을 나타내는 지하수위 자료의 추정을 위해서 제한적 최대 우도치를 이용하는 universal kriging을 사용하였다. 제한적 최대우도법의 우수성을 판정하기 위해 가중 최소자승법을 이용하는 IRD-k와 비교 검토하였다. 교차 타당성에 있어서 RML과 k계 고유 확율함수는 거의 비슷한 결과를 갖고, 참값 대 추정치의 이산분포도와 지하수위 등고선도에 있어서도 2가지 방법이 거의 같은 결과를 만들었다. RNL을 이요한 universal kriging과 가중 최소자승법을 이용한 IRF-k가 비정상 함수자료의 추정에 있어서 거의 비슷한 결과를 만든 원인은 이용된 실험자료의 비정규분포와 적은 자료수에 기인하는 것으로 사료된다.

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이동 위성 채널에서 효율적인 Punctured TCM 방식 (An efficient punctured-coded TCM for the mobile satellite channel)

  • 박성경;김종일;홍성권;주판유;강창언
    • 한국통신학회논문지
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    • 제21권8호
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    • pp.2063-2076
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    • 1996
  • In this thesis, in order to apply a punctured convolutional codes to the trellis coded modulation(TCM), an efficient punctured trellis coded modulation(PTCM) based on the decomposition of the metric into orthogonal components is presented. Also, a simulation is performed in an additive white Gaussian noise(AWGN) and a rician fading channel modeling the mobile satellite channel. The PTCM combines punctured convolutional coding with MPSK modulation to provide a large coding gain in a power-limited or bandwidth-limited channel. However, in general the use of the punctured convolutional code structure in the decoder results in a performance loss in comparison to trellis codes, due to difficulties in assigning metrics. But, the study shows no loss in performance for punctured trellis coded MPSK in comparison to TCM, and what is more, the punctured convolutional codes results in some savings in the complexity of Viterbi decoders, compared to TCM of the same rate. Also, the results shows that the punctured trellis coded .pi./8 shift 8PSK is an attractive scheme for power-limited and band-limited systems and especially, the Viterbi decoder with first and Lth phase difference metrics improves BER performance by the mobile satellite channel.

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압전 작동기/감지기를 이용한 평판의 혼합형 능동 진동제어 기술 (Hybrid Technique for Active Vibration Control of Plate using Piezoceramic Actuators/Sensors)

  • 김영식;이철;김인수
    • 소음진동
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    • 제10권6호
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    • pp.1048-1058
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    • 2000
  • 본 논문에서는 압전 세라믹 재료를 작동기 및 감지기로 이용한 사각 경계면이 고정된 얇은 사각평판의 능동 진동제어 방법을 제시한다. 실험 데이터에 기초한 다중 입출력계의 주파수영역 모델링방법을 이용하여 분포된 센서 및 구동기 특성이 포함된 구조물의 동적 특성이 규명된다. 제어기 구조로는 혼합형을 채택하고 되먹임 제어기는 LQG 제어기법에 의해 설계된다. 앞먹임 제어기는 다중 filtered-$x$ 최소자승오차법에 의해 적응되도록 한다. 진동제어에 대한 시뮬레이션 및 실험결과는 제안된 제어기법이 지속적 외란 및 과도적 외란에 효율적으로 적용될 수 있음을 보인다.

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확률기반 배경제거 기법의 향상을 위한 밝기 사영 및 변환에너지 기반 그림자 영역 제거 방법 (A Shadow Region Suppression Method using Intensity Projection and Converting Energy to Improve the Performance of Probabilistic Background Subtraction)

  • 황숭민;강동중
    • 제어로봇시스템학회논문지
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    • 제16권1호
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    • pp.69-76
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    • 2010
  • The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

자기공명영상의 비지도 분할을 위한 통계적 모델기반 적응적 방법 (A Statistically Model-Based Adaptive Technique to Unsupervised Segmentation of MR Images)

  • 김태우
    • 한국정보처리학회논문지
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    • 제7권1호
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    • pp.286-295
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    • 2000
  • 본 논문은 MR 영상의 비지도 분할을 위하여 MDL원리를 이용한 통계적 모델기반의 적응적 방법을 제안한다. 이 방법에서 조직 영역을 MRF로 모델링함으로써 잡음에 대응하고, 창으로 정의되는 국소영역 내의 밝기값을 가우스 혼합으로 모델링함으로써 영상의 비균일성을 흡수한다. 분할 알고리즘은 ICM을 기반으로 하며 MAP를 근사적으로 추정하고, 모델 파라미터를 국소영역으로부터 구한다. 파라미터 추정과 분할을 위한 창의 크기는 MDL원리를 이용하여 영상으로부터 추정한다. 실험에서 제안한 방법이 특히 비균일성이 있는 MR영상의 분할에서 국소영역의 영상특성을 잘 반영하였으며, 기존의 방법보다 더 좋은 결과를 보여주었다.

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스텝 인덱스 멀티모드 광섬유의 투광 조도분포 모델링 (Modeling of Transmitting Light Irradiance Distribution of Step-index Multimode Optical Fiber)

  • 신우철;홍준희
    • 한국광학회지
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    • 제17권2호
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    • pp.136-142
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    • 2006
  • 광강도 변조방식 광섬유 센서의 변위응답해석에 필요한 투광 조도분포를 수학적으로 모델링 하였다. 유도된 조도분포 모델은 스텝인덱스 멀티모드 광섬유를 대상으로 하며 실험적 검증을 통해 타당성을 확인하였다. 검증된 조도분포 모델을 적용하여 얻은 광섬유 센서의 변위응답 해석결과를 변위측정 결과와 비교하여 거의 일치함을 확인하였다. 또한 기존의 가우시안 조도분포 모델을 적용한 해석결과와 비교했을 때 제안한 조도분포 모델이 보다 정확한 결과를 나타냄을 보이고 있다.

곡가공 프로세스를 고려한 곡판 분류 알고리즘 (An Algorithm of Curved Hull Plates Classification for the Curved Hull Plates Forming Process)

  • 노재규;신종계
    • 대한조선학회논문집
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    • 제46권6호
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    • pp.675-687
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    • 2009
  • In general, the forming process of the curved hull plates consists of sub tasks, such as roll bending, line heating, and triangle heating. In order to complement the automated curved hull forming system, it is necessary to develop an algorithm to classify the curved hull plates of a ship into standard shapes with respect to the techniques of forming task, such as the roll bending, the line heating, and the triangle heating. In this paper, the curved hull plates are classified by four standard shapes and the combination of them, or saddle, convex, flat, cylindrical shape, and the combination of them, that are related to the forming tasks necessary to form the shapes. In preprocessing, the Gaussian curvature and the mean curvature at the mid-point of a mesh of modeling surface by Coon's patch are calculated. Then the nearest neighbor method to classify the input plate type is applied. Tests to verify the developed algorithm with sample plates of a real ship data have been performed.