• 제목/요약/키워드: Bayesian model

검색결과 1,312건 처리시간 0.032초

접는 날개에 대한 모드시험/해석결과 보정 (Modal teat/analysis result correlation of folding fin)

  • 양해석
    • 소음진동
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    • 제6권3호
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    • pp.305-315
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    • 1996
  • Present paper aims at the correlation of modal characteristics of folding fin between test and analysis using an optimization theory. Folding fin is composed of a movable fin, a base fin, and many functional components related to the folding mechanism. Joint parts of folding fin in FEM are initially modeled as rigid elements resulting some difference between test and analysis in modal characteristics. Therefore, some equivalent springs representing joint parts are introduced to improve the FEM model. The springs were set as design variables, while the frequency difference between test and analysis was set as the object function. Bayesian procedure was ujsed for the minimization.

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그리드지도의 방향정보 이용한 형상지도형성 (Feature Map Construction using Orientation Information in a Grid Map)

  • 송도성;강승균;임종환
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2004년도 추계학술대회 논문집
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    • pp.1496-1499
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    • 2004
  • The paper persents an efficient method of extracting line segment in a grid map. The grid map is composed of 2-D grids that have both the occupancy and orientation probabilities based on the simplified Bayesian updating model. The probabilities and orientations of cells in the grid map are continuously updated while the robot explorers to their values. The line segments are, then, extracted from the clusters using Hough transform methods. The eng points of a line segment are evaluated from the cells in each cluster, which is simple and efficient comparing to existing methods. The proposed methods are illustrated by sets of experiments in an indoor environment.

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Asset Price, the Exchange Rate, and Trade Balances in China: A Sign Restriction VAR Approach

  • Kim, Wongi
    • East Asian Economic Review
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    • 제22권3호
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    • pp.371-400
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    • 2018
  • Although asset price is an important factor in determining changes in external balances, no studies have investigated it from the Chinese perspective. In this study, I empirically examine the underlying driving forces of China's trade balances, particularly the role of asset price and the real exchange rate. To this end, I estimate a sign-restricted structural vector autoregressive model with quarterly time series data for China, using the Bayesian method. The results show that changes in asset price affect China's trade balances through private consumption and investment. Also, an appreciation of the real exchange rate tends to deteriorate trade balances in China. Furthermore, forecast error variance decomposition results indicate that changes in asset price (stock price and housing price) explain about 20% variability of trade balances, while changes in the real exchange rate can explain about 10%.

베이지안 네트워크를 이용한 자동차 시뮬레이션 (Simulation of Automobile Model Using Bayesian Network)

  • 김태현;손민우;신동규;신동일
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2007년도 한국컴퓨터종합학술대회논문집 Vol.34 No.1 (C)
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    • pp.328-331
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    • 2007
  • 본 논문은 물리엔진을 기반으로 구현한 자동차 시뮬레이터 프로그램에서 베이지안 네트워크를 이용해서 최적화된 이동방식을 계산하여 제공하는 기능을 구현한 결과를 보여준다. 자동차 시뮬레이터로부터 입력 받은 각 코스별 통과시간과 이동위치 및 회전각을 토대로 수집된 정보에 베이지안 네트워크를 적용하여 가장 빠른 시간 내에 완주한 코스의 이동위치에 따른 회전각을 산출해 낸 다음 각 위치마다 확률적으로 가장 적합한 핸들 조작법을 화면에 제공함으로써 사용자가 현 위치에 가장 최적화 된 조작법을 알 수 있게 한다. 또한 반복적인 레이스 트랙 완주에 따라서 더욱 최적화 된 각도를 피드백 함으로서 좀 더 빠른 완주가 가능해지도록 하는 것이 이 연구의 목적이다.

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MCE 학습 알고리즘을 이용한 문장독립형 화자식별의 성능 개선 (Performance Improvement of a Text-Independent Speaker Identification System Using MCE Training)

  • 김태진;최재길;권철홍
    • 대한음성학회지:말소리
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    • 제57호
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    • pp.165-174
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    • 2006
  • In this paper we use a training algorithm, MCE (Minimum Classification Error), to improve the performance of a text-independent speaker identification system. The MCE training scheme takes account of possible competing speaker hypotheses and tries to reduce the probability of incorrect hypotheses. Experiments performed on a small set speaker identification task show that the discriminant training method using MCE can reduce identification errors by up to 54% over a baseline system trained using Bayesian adaptation to derive GMM (Gaussian Mixture Models) speaker models from a UBM (Universal Background Model).

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영상분할을 위한 2차원 무한 은닉 마코프 모형의 비모수적 베이스 추정 (Bayesian Parameter Estimation of 2D infinite Hidden Markov Model for Image Segmentation)

  • 김선월;조완현
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(A)
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    • pp.477-479
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    • 2011
  • 본 논문에서는 1차원 은닉 마코프 모델을 2차원으로 확장하기 위하여 노드들의 마코프 특성이 인과적인 관계를 갖는 마코프 메쉬 모델을 이용하여 완전한 2차원 HMM의 구조를 갖는 모델을 제안한다. 마코프메쉬 모델은 이웃시스템을 통하여 이전의 시점을 정의하고, 인과적인 관계를 통하여 전이확률의 계산을 가능하게 한다. 또한 영상의 최적의 분할을 위하여 계층적 디리슐레 과정을 사전분포로 두어 고정된 상태의 수가 아닌 무한의 상태 수를 갖는 2차원 HMM을 제안한다. HDP로 정의된 사전분포와 관측된 표본 자료의 정보를 갖는 우도함수를 결합한 사후분포의 베이스 추정은 깁스샘플링 알고리즘을 이용하여 계산된다.

IL-2 역가의 통계적 추정에 관한 연구 (A Study on statistical inference on IL-2 titer)

  • 박래현;박석영;이석훈
    • 응용통계연구
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    • 제2권2호
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    • pp.27-35
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    • 1989
  • 최근 암의 면역치료 요법에 사용이 활발히 시도되고 있는 IL-2(Interleukin-2)의 역가를 측정하는 문제를 통계적 모형을 통하여 정립하고 그 모형하에서 모수의 함수로 표현되는 역가의 추론과정을 연구하였다. 표준시료와 비교하여, 환자로부터 얻은 미지의 시료의 역가를 구하기 위하여 선형모형을 제시하고 베이지안 기법을 사용하여 계수들의 함수로 나타내지는 역가의 신뢰구간을 구하였으며 실제 데이타에 적용하여 보았다.

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다중반사경로효과를 고려한 자율이동로봇의 초음파지도 형성 (Consideration of Multipath Effect in Sonar Map Construction for an Autonomous Mobile Robot)

  • 임종환;조동우
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.106-112
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    • 1993
  • A new model for the construction of a sonar map in a specular environment has been developed ad implemented. In a real world where most of the object surfaces are specular ones, a sonar sensor suffers from a multipath effect which results in a wrong interpretation of an objects's location. To reduce this effect and hence to construct a reliable map of a robot's surroundings, a probabilistic approach based on Bayesian reasoning is adopted to both evaluation of object orientations and estimation of an occupancy probability of a cell by an object. The usefulness of this approach is illustrated with the results produced by our mobile robot equipped with ultrasonic sensors.

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Visual Object Tracking based on Real-time Particle Filters

  • Lee, Dong- Hun;Jo, Yong-Gun;Kang, Hoon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1524-1529
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    • 2005
  • Particle filter is a kind of conditional density propagation model. Its similar characteristics to both selection and mutation operator of evolutionary strategy (ES) due to its Bayesian inference rule structure, shows better performance than any other tracking algorithms. When a new object is entering the region of interest, particle filter sets which have been swarming around the existing objects have to move and track the new one instantaneously. Moreover, there is another problem that it could not track multiple objects well if they were moving away from each other after having been overlapped. To resolve reinitialization problem, we use competitive-AVQ algorithm of neural network. And we regard interfarme difference (IFD) of background images as potential field and give priority to the particles according to this IFD to track multiple objects independently. In this paper, we showed that the possibility of real-time object tracking as intelligent interfaces by simulating the deformable contour particle filters.

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Customer Behavior Data Model using User Profile Analysis

  • Jung, Yong Gyu;Lee, Agatha;Lee, Jeong Chan;Lee, Young Dae
    • International Journal of Advanced Culture Technology
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    • 제1권2호
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    • pp.13-17
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    • 2013
  • Today, most of the companies have numerous issues to take advantage of the data within the organization. Modeling techniques could be described using profile and historical log data as a tool of data mining techniques. It is covered increasingly with data entry, research, processing, modeling and reporting components of the icon in the form of easy-to-use in many datamining tools. Visual data mining process can create a data stream. In this paper, customer behavior is predicted in pages or products, using the history profile analysis and the navigation items are necessary to predict unknown features.

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