• 제목/요약/키워드: data space approach

검색결과 677건 처리시간 0.03초

Multi-Objective Design Exploration for Multidisciplinary Design Optimization Problems

  • Obayashi Shigeru;Jeong Shinkyu;Chiba Kazuhisa
    • 한국전산유체공학회:학술대회논문집
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    • 한국전산유체공학회 2005년도 추계 학술대회논문집
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    • pp.1-10
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    • 2005
  • A new approach, Multi-Objective Design Exploration (MODE), is presented to address Multidisciplinary Design Optimization (MDO) problems by CFD-CSD coupling. MODE reveals the structure of the design space from the trade-off information and visualizes it as a panorama for Decision Maker. The present form of MODE consists of Kriging Model, Adaptive Range Multi Objective Genetic Algorithms, Analysis of Variance and Self-Organizing Map. The main emphasis of this approach is visual data mining. An MDO system using high fidelity simulation codes, Navier-Stokes solver and NASTRAN, has been developed and applied to a regional-jet wing design. Because the optimization system becomes very computationally expensive, only brief exploration of the design space has been performed. However, data mining result demonstrates that design knowledge can produce a good design even from the brief design exploration.

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An Al Approach with Tabu Search to solve Multi-level Knapsack Problems:Using Cycle Detection, Short-term and Long-term Memory

  • Ko, Il-Sang
    • 한국경영과학회지
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    • 제22권3호
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    • pp.37-58
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    • 1997
  • An AI approach with tabu search is designed to solve multi-level knapsack problems. The approach performs intelligent actions with memories of historic data and learning effect. These action are developed ont only by observing the attributes of the optimal solution, the solution space, and its corresponding path to the optimal, but also by applying human intelligence, experience, and intuition with respect to the search strategies. The approach intensifies, or diversifies the search process appropriately in time and space. In order to create a good neighborhood structure, this approach uses two powerful choice rules that emphasize the impact of candidate variables on the current solution with respect to their profit contribution. "Pseudo moves", similar to "aspirations", support these choice rules during the evaluation process. For the purpose of visiting as many relevant points as possible, strategic oscillation between feasible and infeasible solutions around the boundary is applied. To avoid redundant moves, short-term (tabu-lists), intemediate-term (cycle-detection), and long-term (recording frequency and significant solutions for diversfication) memories are used. Test results show that among the 45 generated problems (these problems pose significant or insurmountable challenges to exact methods) the approach produces the optimal solutions in 39 cases.lutions in 39 cases.

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형상보건을 이용한 유한요소 격자생성

  • 이원양;최영;조성욱
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1994년도 추계학술대회 논문집
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    • pp.298-302
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    • 1994
  • A three dimensional FE mesh generation scheme based on mapping approach is proposed in this study. A volume in Euclcdian space is represented by composite hyperpatches which are piecewise cubic functions with parameters u,v,w. A key idea in the proposed approach is that sampled grid data points only on the boundary surfaces are needed for the shape representation. Inner points which are necessary of form a hyperpatch are internally generated by Coons patches. This approach is most appropriate for the shapes which are compositions of hexahedron-like shapes and also severely curved.

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Loose Coupling Approach of CFD with a Free-Wake Panel Method for Rotorcraft Applications

  • Lee, Jae-Won;Oh, Se-Jong;Yee, Kwan-Jung;Kim, Sang-Hun;Lee, Dong-Ho
    • International Journal of Aeronautical and Space Sciences
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    • 제8권1호
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    • pp.1-9
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    • 2007
  • As a first step toward a complete CFD-CSD coupling for helicopter rotor load analysis, the present study attempts to loosely couple a CFD code with a source-double panel method. The far-field wake effects were calculated by a time-marching free vortex wake method and were implemented into the CFD module via field velocity approach. Unlike the lifting line method, the air loads correction process is not trivial for the source-doublet panel method. The air loads correction process between the source-doublet method and CFD is newly suggested in this work and the computation results are validated against available data for well-known hovering flight conditions.

음성인식을 위한 변환 공간 모델에 근거한 순차 적응기법 (Sequential Adaptation Algorithm Based on Transformation Space Model for Speech Recognition)

  • 김동국;장준혁;김남수
    • 음성과학
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    • 제11권4호
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    • pp.75-88
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    • 2004
  • In this paper, we propose a new approach to sequential linear regression adaptation of continuous density hidden Markov models (CDHMMs) based on transformation space model (TSM). The proposed TSM which characterizes the a priori knowledge of the training speakers associated with maximum likelihood linear regression (MLLR) matrix parameters is effectively described in terms of the latent variable models. The TSM provides various sources of information such as the correlation information, the prior distribution, and the prior knowledge of the regression parameters that are very useful for rapid adaptation. The quasi-Bayes (QB) estimation algorithm is formulated to incrementally update the hyperparameters of the TSM and regression matrices simultaneously. Experimental results showed that the proposed TSM approach is better than that of the conventional quasi-Bayes linear regression (QBLR) algorithm for a small amount of adaptation data.

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Improved GPS-based Satellite Relative Navigation Using Femtosecond Laser Relative Distance Measurements

  • Oh, Hyungjik;Park, Han-Earl;Lee, Kwangwon;Park, Sang-Young;Park, Chandeok
    • Journal of Astronomy and Space Sciences
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    • 제33권1호
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    • pp.45-54
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    • 2016
  • This study developed an approach for improving Carrier-phase Differential Global Positioning System (CDGPS) based realtime satellite relative navigation by applying laser baseline measurement data. The robustness against the space operational environment was considered, and a Synthetic Wavelength Interferometer (SWI) algorithm based on a femtosecond laser measurement model was developed. The phase differences between two laser wavelengths were combined to measure precise distance. Generated laser data were used to improve estimation accuracy for the float ambiguity of CDGPS data. Relative navigation simulations in real-time were performed using the extended Kalman filter algorithm. The GPS and laser-combined relative navigation accuracy was compared with GPS-only relative navigation solutions to determine the impact of laser data on relative navigation. In numerical simulations, the success rate of integer ambiguity resolution increased when laser data was added to GPS data. The relative navigational errors also improved five-fold and two-fold, relative to the GPS-only error, for 250 m and 5 km initial relative distances, respectively. The methodology developed in this study is suitable for application to future satellite formation-flying missions.

ERS-1 AND CCRS C-SAR Data Integration For Look Direction Bias Correction Using Wavelet Transform

  • Won, J.S.;Moon, Woo-Il M.;Singhroy, Vern;Lowman, Paul-D.Jr.
    • 대한원격탐사학회지
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    • 제10권2호
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    • pp.49-62
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    • 1994
  • Look direction bias in a single look SAR image can often be misinterpreted in the geological application of radar data. This paper investigates digital processing techniques for SAR image data integration and compensation of the SAR data look direction bias. The two important approaches for reducing look direction bias and integration of multiple SAR data sets are (1) principal component analysis (PCA), and (2) wavelet transform(WT) integration techniques. These two methods were investigated and tested with the ERS-1 (VV-polarization) and CCRS*s airborne (HH-polarization) C-SAR image data sets recorded over the Sudbury test site, Canada. The PCA technique has been very effective for integration of more than two layers of digital image data. When there only two sets of SAR data are available, the PCA thchnique requires at least one more set of auxiliary data for proper rendition of the fine surface features. The WT processing approach of SAR data integration utilizes the property which decomposes images into approximated image ( low frequencies) characterizing the spatially large and relatively distinct structures, and detailed image (high frequencies) in which the information on detailed fine structures are preserved. The test results with the ERS-1and CCRS*s C-SAR data indicate that the new WT approach is more efficient and robust in enhancibng the fine details of the multiple SAR images than the PCA approach.

데이터 지역성 메커니즘을 이용한 지역 스토리지 용량 관리 방법 (A Method to Manage Local Storage Capacity Using Data Locality Mechanism)

  • 김바울;구민오;민덕기
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2013년도 추계학술대회
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    • pp.324-327
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    • 2013
  • 최근 클라우드 컴퓨팅 기술의 발달로 인해 클라우드 기반의 컴퓨팅 자원의 활용은 다양한 분야에서 실생활에 적용되고 있다. 특히, 스마트 기기의 기술과 네트워크 인프라의 발달은 지역 스마트 디바이스와 클라우드 저장소간의 파일 공유에 대한 필요성을 더욱 촉진 시켰다. 하지만, 스마트 기기의 저장 공간 제약 사항으로 인해 클라우드 저장소에 파일을 저장하는 것은 지역 저장소의 저장 공간기아 문제를 촉발 시킨다. 이것은 클라우드 저장소 서비스에서 대용량의 파일 저장 공간을 제공하더라도 사용자는 저장소 부족 문제에 직면 할 수 있음을 의미한다. 본 연구에서는 스마트 기기와 클라우드 저장소간의 파일 관리 방법을 제시한다. 본 연구에서 제시하는 지역 스토리지 용량 관리 방법은 사용자의 최근 사용한 날짜를 기반으로 파일 사용 패턴을 계산하고 이를 기반으로 지역에 저장된 파일들 중 마이그레이션 되어야 할 대상들을 선정하는 방법을 사용하고 있다. 더욱이 본 연구에서 제시하는 방법을 통하여 대규모 빅 데이터 저장소와 저장 공간의 제약을 가지고 있는 지역의 소형 클라이언트 장치간의 파일 동기화에도 활용될 수 있다.

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A Multi-Objective TRIBES/OC-SVM Approach for the Extraction of Areas of Interest from Satellite Images

  • Benhabib, Wafaa;Fizazi, Hadria
    • Journal of Information Processing Systems
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    • 제13권2호
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    • pp.321-339
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    • 2017
  • In this work, we are interested in the extraction of areas of interest from satellite images by introducing a MO-TRIBES/OC-SVM approach. The One-Class Support Vector Machine (OC-SVM) is based on the estimation of a support that includes training data. It identifies areas of interest without including other classes from the scene. We propose generating optimal training data using the Multi-Objective TRIBES (MO-TRIBES) to improve the performances of the OC-SVM. The MO-TRIBES is a parameter-free optimization technique that manages the search space in tribes composed of agents. It makes different behavioral and structural adaptations to minimize the false positive and false negative rates of the OC-SVM. We have applied our proposed approach for the extraction of earthquakes and urban areas. The experimental results and comparisons with different state-of-the-art classifiers confirm the efficiency and the robustness of the proposed approach.