• Title/Summary/Keyword: Problem Decomposition

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Role of Artificial Neural Networks in Multidisciplinary Optimization and Axiomatic Design

  • Lee, Jong-Soo
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.695-700
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    • 2008
  • Artificial neural network (ANN) has been extensively used in areas of nonlinear system modeling, analysis and design applications. Basically, ANN has its distinct capabilities of implementing system identification and/or function approximation using a number of input/output patterns that can be obtained via numerical and/or experimental manners. The paper describes a role of ANN, especially a back-propagation neural network (BPN) in the context of engineering analysis, design and optimization. Fundamental mechanism of BPN is briefly summarized in terms of training procedure and function approximation. The BPN based causality analysis (CA) is further discussed to realize the problem decomposition in the context of multidisciplinary design optimization. Such CA is also applied to quantitatively evaluate the uncoupled or decoupled design matrix in the context of axiomatic design with the independence axiom.

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Train-Fleet Assignment based on Public Interests (공공성을 고려한 열차용량 할당)

  • Oh Seog-Moon;Son Moo-Sung;Choi In-Chan;Choi In-Sang
    • Journal of the Korean Society for Railway
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    • v.8 no.6 s.31
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    • pp.602-609
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    • 2005
  • In this paper, we consider the train-fleet assignment problem to determine fleet assignment and seat allocation synchronously. An integer programming model of the problem and a decomposition-based solution approach are developed to handle short-term period deterministic orgin-destination demands. The primary objective used in the developed model is to maximize the total number of passengers transported during peak load periods, such as Chuseok national holiday period. Thus, in developing the model we choose to profit-pursuing system. We also show how the proposed model can be readily modified to incorporate profit-maximization. Using the empirical data sets provided by a Korean railroad company, we have tested the proposed solution approach and carried out various comparison analyses by varying traffic demand patterns and train schedules. The computational experiments reveal that the proposed solutions approach produces high quality solutions in reasonable computation time.

Thermal decomposition and ablation analysis of solid rocket propulsion (삭마 및 열분해 반응을 고려한 고체 추진기관의 열해석)

  • Kim, Yun-Chul
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2010.05a
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    • pp.113-122
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    • 2010
  • A two-dimensional thermal response and ablation analysis code for predicting charring material ablation and shape change on solid rocket nozzle is presented. For closing the problem of thermal analysis, Arrhenius' equation and Zvyagin's ablation model are used. The moving boundary problem are solved by remeshing-rezoning method. For simulation of complicated thermal protection systems, this method is integrated with a three-dimensional finite-element thermal and structure analysis code through continuity of temperature and heat flux.

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Semidefinite Spectral Clustering (준정부호 스펙트럼의 군집화)

  • Kim, Jae-Hwan;Choi, Seung-Jin
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07a
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    • pp.892-894
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    • 2005
  • Graph partitioning provides an important tool for data clustering, but is an NP-hard combinatorial optimization problem. Spectral clustering where the clustering is performed by the eigen-decomposition of an affinity matrix [1,2]. This is a popular way of solving the graph partitioning problem. On the other hand, semidefinite relaxation, is an alternative way of relaxing combinatorial optimization. issuing to a convex optimization[4]. In this paper we present a semidefinite programming (SDP) approach to graph equi-partitioning for clustering and then we use eigen-decomposition to obtain an optimal partition set. Therefore, the method is referred to as semidefinite spectral clustering (SSC). Numerical experiments with several artificial and real data sets, demonstrate the useful behavior of our SSC. compared to existing spectral clustering methods.

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Reconstruction of missing response data for identification of higher modes

  • Shrikhande, Manish
    • Earthquakes and Structures
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    • v.2 no.4
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    • pp.323-336
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    • 2011
  • The problem of reconstruction of complete building response from a limited number of response measurements is considered. The response at the intermediate degrees of freedom is reconstructed by using piecewise cubic Hermite polynomial interpolation in time domain. The piecewise cubic Hermite polynomial interpolation is preferred over the spline interpolation due to its trend preserving character. It has been shown that factorization of response data in variable separable form via singular value decomposition can be used to derive the complete set of normal modes of the structural system. The time domain principal components can be used to derive empirical transfer functions from which the natural frequencies of the structural system can be identified by peak-picking technique. A reduced-rank approximation for the system flexibility matrix can be readily constructed from the identified mass-orthonormal mode shapes and natural frequencies.

Estimating People's Position Using Matrix Decomposition

  • Dao, Thi-Nga;Yoon, Seokhoon
    • International journal of advanced smart convergence
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    • v.8 no.2
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    • pp.39-46
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    • 2019
  • Human mobility estimation plays a key factor in a lot of promising applications including location-based recommendation systems, urban planning, and disease outbreak control. We study the human mobility estimation problem in the case where recent locations of a person-of-interest are unknown. Since matrix decomposition is used to perform latent semantic analysis of multi-dimensional data, we propose a human location estimation algorithm based on matrix factorization to reconstruct the human movement patterns through the use of information of persons with correlated movements. Specifically, the optimization problem which minimizes the difference between the reconstructed and actual movement data is first formulated. Then, the gradient descent algorithm is applied to adjust parameters which contribute to reconstructed mobility data. The experiment results show that the proposed framework can be used for the prediction of human location and achieves higher predictive accuracy than a baseline model.

ILLUMINATION ADUSTMENT FOR BRIDGE COATING IMAGES USING BEMD-MORPHOLOGY APPROACH

  • Po-Han Chen;Ya-Ching Yang;Luh-Maan Chang
    • International conference on construction engineering and project management
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    • 2009.05a
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    • pp.224-229
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    • 2009
  • Digital image recognition has been used for steel bridge surface assessment since late 1990s. However, the non-uniform illumination problems such as shades, shadows, and highlights are still challenges in image processing to date. Therefore, this paper develops a new approach to tackle the non-uniform illumination problem for rust image adjustment. The inhomogeneous illumination problem is divided into shades/shadows and highlights in this paper. The proposed BEMD-morphology approach (BMA) utilizes the bidimensional empirical mode decomposition to mitigate the shade/shadow effect, and the morphological processing to detect and replace the highlight area. Finally, the rust image processed with the BMA will be segmented by the K-Means algorithm, one of the most popular and effective methods, to show the effectiveness of illumination adjustment.

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A DIRECT SOLVER FOR THE LEGENDRE TAU APPROXIMATION FOR THE TWO-DIMENSIONAL POISSON PROBLEM

  • Jun, Se-Ran;Kang, Sung-Kwon;Kwon, Yong-Hoon
    • Journal of applied mathematics & informatics
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    • v.23 no.1_2
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    • pp.25-42
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    • 2007
  • A direct solver for the Legendre tau approximation for the two-dimensional Poisson problem is proposed. Using the factorization of symmetric eigenvalue problem, the algorithm overcomes the weak points of the Schur decomposition and the conventional diagonalization techniques for the Legendre tau approximation. The convergence of the method is proved and numerical results are presented.

A study on the mathematical model of the long-term track tamping scheduling problem (궤도 다짐작업의 장기 일정계획문제에 관한 수리적 모형 고찰)

  • Oh Seog- Moon;Lee Ji-Ha;Park Bum Hwan;Lee Hee-up;Hong Soon-Heum
    • Proceedings of the KSR Conference
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    • 2005.11a
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    • pp.1130-1137
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    • 2005
  • This paper addresses the mathematical model of the long-term track tamping scheduling problem in the railway system. The proposed model is analyzed in problem size, then three solution approaches (relaxation, decomposition, and heuristic) are presented at the sketch level.

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The Optimal Subchannel and Bit Allocation for Multiuser OFDM System: A Dual-Decomposition Approach (다중 사용자 OFDM 시스템의 최적 부채널 및 비트 할당: Dual-Decomposition 방법)

  • Park, Tae-Hyung;Im, Sung-Bin;Seo, Man-Jung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.1C
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    • pp.90-97
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    • 2009
  • The advantages of the orthogonal frequency division multiplexing (OFDM) are high spectral efficiency, resiliency to RF interference, and lower multi-path distortion. To further utilize vast channel capacity of the multiuser OFDM, one has to find the efficient adaptive subchannel and bit allocation among users. In this paper, we propose an 0-1 integer programming model formulating the optimal subchannel and bit allocation problem of the multiuser OFDM. We employ a dual-decomposition method that provides a tight linear programming (LP) relaxation bound. Simulation results are provided to show the effectiveness of the 0-1 integer programming model. MATLAB simulation on a system employing M-ary quardarature amplitude modulation (MQAM) assuming a frequency-selective channel consisting of three independent Rayleigh multi-paths are carried with the optimal subchannel and bit allocation solution generated by 0-1 integer programming model.