• Title/Summary/Keyword: Global Method

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A New Method of the Global Interpolation in NURBS Surface (NURBS Surface Global Interpolation에 대한 한 방법)

  • 정형배;나승수;박종환
    • Korean Journal of Computational Design and Engineering
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    • v.2 no.4
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    • pp.237-243
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    • 1997
  • A new method is introduced for the interpolation in NURBS Surface. This method uses the basis functions to assign the parameter values to the arbitrary set of geometric data and uses the iteration method to compute the control net. The advantages of this method are the feasible transformation of the data set to the matrix form and the effective surface generation as a result, especially to the design engineer.

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AN ADAPTIVE APPROACH OF CONIC TRUST-REGION METHOD FOR UNCONSTRAINED OPTIMIZATION PROBLEMS

  • FU JINHUA;SUN WENYU;SAMPAIO RAIMUNDO J. B. DE
    • Journal of applied mathematics & informatics
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    • v.19 no.1_2
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    • pp.165-177
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    • 2005
  • In this paper, an adaptive trust region method based on the conic model for unconstrained optimization problems is proposed and analyzed. We establish the global and super linear convergence results of the method. Numerical tests are reported that confirm the efficiency of the new method.

CONVERGENCE OF THE NONMONOTONE PERRY-SHANNO METHOD FOR UNCONSTRAINED OPTIMIZATION

  • Ou, Yigui;Ma, Wei
    • Journal of applied mathematics & informatics
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    • v.30 no.5_6
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    • pp.971-980
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    • 2012
  • In this paper, a method associating with one new form of nonmonotone linesearch technique is proposed, which can be regarded as a generalization of the Perry-Shanno memoryless quasi-Newton type method. Under some reasonable conditions, the global convergence of the proposed method is proven. Numerical tests show its efficiency.

The Sementic Network Analysis of Elementary Students' Perceptions about Global Environment (초등학생들의 지구환경 인식에 대한 네트워크 분석)

  • Lee, Sanggyun;kim, Soonshik
    • Journal of the Korean Society of Earth Science Education
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    • v.11 no.3
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    • pp.212-223
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    • 2018
  • The purpose of this study is to investigate the perception of elementary students' 'global environment'. The research method used the Sementic Network Analysis method of the global environment elements which appeared in the students' explanation about the picture and the picture that emerged about the 'global environment'. The results of the study are as follows. First, as a result of analyzing the students' explanation of the pictures along with the pictures of the students, the elementary students were perceived negatively about the global environment such as 'environmental pollution', 'global warming' and 'trash problem'. Second, as a result of analyzing the image of the global environment expressed in the picture, there were many images expressed from a everyday viewpoint rather than a macroscopic viewpoint, and there was a tendency to express the earth personified. In addition, the picture expressing the clean earth environment expressed the most trees with natural environment elements and expressed the healthy earth with various natural elements such as sea, mountain, and land. Third, as a result of analyzing the difference of perception of global environment by grade, it was found that the difference of perception of global environment by grade was not much different.

Performance Improvement of Genetic Algorithms through Fusion of Queen-bee Evolution into the Rank-based Control of Mutation Probability (등급기준 돌연변이 확률조절에 여왕벌진화의 융합을 통한 유전자알고리즘의 성능 향상)

  • Jung, Sung-Hoon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.49 no.4
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    • pp.54-61
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    • 2012
  • This paper proposes a fusion method of the queen-bee evolution into the rank-based control of mutation probability for improving the performances of genetic algorithms. The rank-based control of mutation probability which showed some performance improvements than the original method was a method that prevented individuals of genetic algorithms from falling into local optimum areas and also made it possible for the individuals to get out of the local optimum areas if they fell into there. This method, however, showed not good performances at the optimization problems that had a global optimum located in a small area regardless of the number of local optimum areas. We think that this is because the method is insufficient in the convergence into the global optimum, so propose a fusion method of the queen-bee evolution into this method in this paper. The queen-bee evolution inspired by reproduction process of queen-bee is a method that can strengthen the convergency of genetic algorithms. From the extensive experiments with four function optimization problems in order to measure the performances of proposed method we could find that the performances of proposed method was considerably good at the optimization problems whose global optimum is located in a small area as we expected. Our method, however, showed not good performances at the problems whose global optima were distributed in broad ranges and even showed bad performances at the problems whose global optima were located far away. These results indicate that our method can be effectively used at the problems whose global optimum is located in a small area.

MULTI-STAGE AERODYNAMIC DESIGN OF AIRCRAFT GEOMETRIES BY KRIGING-BASED MODELS AND ADJOINT VARIABLE APPROACH (Kriging 기반 모델과 매개변수(Adjoint Variable)법을 이용한 항공기형상의 2단계 공력최적설계)

  • Yim, J.W.;Lee, B.J.;Kim, C.
    • 한국전산유체공학회:학술대회논문집
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    • 2009.04a
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    • pp.57-65
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    • 2009
  • An efficient and high-fidelity design approach for wing-body shape optimization is presented. Depending on the size of design space and the number of design of variable, aerodynamic shape optimization process is carried out via different optimization strategies at each design stage. In the first stage, global optimization techniques are applied to planform design with a few geometric design variables. In the second stage, local optimization techniques are used for wing surface design with a lot of design variables to maintain a sufficient design space with a high DOF (Degree of Freedom) geometric change. For global optimization, Kriging method in conjunction with Genetic Algorithm (GA) is used. Asearching algorithm of EI (Expected Improvement) points is introduced to enhance the quality of global optimization for the wing-planform design. For local optimization, a discrete adjoint method is adopted. By the successive combination of global and local optimization techniques, drag minimization is performed for a multi-body aircraft configuration while maintaining the baseline lift and the wing weight at the same time. Through the design process, performances of the test models are remarkably improved in comparison with the single stage design approach. The performance of the proposed design framework including wing planform design variables can be efficiently evaluated by the drag decomposition method, which can examine the improvement of various drag components, such as induced drag, wave drag, viscous drag and profile drag.

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Sequential Point Cloud Generation Method for Efficient Representation of Multi-view plus Depth Data (다시점 영상 및 깊이 영상의 효율적인 표현을 위한 순차적 복원 기반 포인트 클라우드 생성 기법)

  • Kang, Sehui;Han, Hyunmin;Kim, Binna;Lee, Minhoe;Hwang, Sung Soo;Bang, Gun
    • Journal of Korea Multimedia Society
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    • v.23 no.2
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    • pp.166-173
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    • 2020
  • Multi-view images, which are widely used for providing free-viewpoint services, can enhance the quality of synthetic views when the number of views increases. However, there needs an efficient representation method because of the tremendous amount of data. In this paper, we propose a method for generating point cloud data for the efficient representation of multi-view color and depth images. The proposed method conducts sequential reconstruction of point clouds at each viewpoint as a method of deleting duplicate data. A 3D point of a point cloud is projected to a frame to be reconstructed, and the color and depth of the 3D point is compared with the pixel where it is projected. When the 3D point and the pixel are similar enough, then the pixel is not used for generating a 3D point. In this way, we can reduce the number of reconstructed 3D points. Experimental results show that the propose method generates a point cloud which can generate multi-view images while minimizing the number of 3D points.