• 제목/요약/키워드: linear algorithm

검색결과 4,034건 처리시간 0.029초

Genetic algorithm based optimum design of non-linear steel frames with semi-rigid connections

  • Hayalioglu, M.S.;Degertekin, S.O.
    • Steel and Composite Structures
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    • 제4권6호
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    • pp.453-469
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    • 2004
  • In this article, a genetic algorithm based optimum design method is presented for non-linear steel frames with semi-rigid connections. The design algorithm obtains the minimum weight frame by selecting suitable sections from a standard set of steel sections such as European wide flange beams (i.e., HE sections). A genetic algorithm is employed as optimization method which utilizes reproduction, crossover and mutation operators. Displacement and stress constraints of Turkish Building Code for Steel Structures (TS 648, 1980) are imposed on the frame. The algorithm requires a large number of non-linear analyses of frames. The analyses cover both the non-linear behaviour of beam-to-column connection and $P-{\Delta}$ effects of beam-column members. The Frye and Morris polynomial model is used for modelling of semi-rigid connections. Two design examples with various type of connections are presented to demonstrate the application of the algorithm. The semi-rigid connection modelling results in more economical solutions than rigid connection modelling, but it increases frame drift.

고속순차 최소자승법에 의한 선형위상 유한응답 여파기의 설계 (Fast Sequential Least Squares Design of FIR Filters with Linear Phase)

  • 선우종성
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1987년도 학술발표회 논문집
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    • pp.79-81
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    • 1987
  • In this paper we propose a fast adaptive least squares algorithm for linear phase FIR filters. The algorithm requires 10m multiplications per data point where m is the filter order. Both linear phase cases with constant phase delay and constant group delay are examined. Simulation results demonstrate that the proeposed algorithm is superior to the LMS gradient algorithm and the averaging scheme used for the modified fast Kalman algorithm.

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Application of an Optimization Method to Groundwater Contamination Problems

  • Ko, Nak-Youl;Lee, Jin-Yong;Lee, Kang-Kun
    • 한국지하수토양환경학회:학술대회논문집
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    • 한국지하수토양환경학회 2002년도 추계학술발표회
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    • pp.24-27
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    • 2002
  • The optimal designs of groundwater problems of contaminant containment and cleanup using linear programming and genetic algorithm are provided. In the containment problem, genetic algorithm shows the superior feature to linear programming. In cleanup problem, genetic algorithm makes reasonable optimal design. Un this study, it is demonstrated through numerical experiments that genetic algorithm can be applied to remedial designs of groundwater problems.

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Parameters estimation of the generalized linear failure rate distribution using simulated annealing algorithm

  • Sarhan, Ammar M.;Karawia, A.A.
    • International Journal of Reliability and Applications
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    • 제13권2호
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    • pp.91-104
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    • 2012
  • Sarhan and Kundu (2009) introduced a new distribution named as the generalized linear failure rate distribution. This distribution generalizes several well known distributions. The probability density function of the generalized linear failure rate distribution can be right skewed or unimodal and its hazard function can be increasing, decreasing or bathtub shaped. This distribution can be used quite effectively to analyze lifetime data in place of linear failure rate, generalized exponential and generalized Rayleigh distributions. In this paper, we apply the simulated annealing algorithm to obtain the maximum likelihood point estimates of the parameters of the generalized linear failure rate distribution. Simulated annealing algorithm can not only find the global optimum; it is also less likely to fail because it is a very robust algorithm. The estimators obtained using simulated annealing algorithm have been compared with the corresponding traditional maximum likelihood estimators for their risks.

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등가정하중을 이용한 구조최적설계 방법을 이용한 비선형 거동구조물의 최적설계 (Non-linear Structural Optimization Using NROESL)

  • 박기종;박경진
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2004년도 추계학술대회 논문집
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    • pp.1256-1261
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    • 2004
  • Nonlinear Response Optimization using Equivalent Static Loads (NROESL) method/algorithm is proposed to perform optimization of non-linear response structures. It is more expensive to carry out nonlinear response optimization than linear response optimization. The conventional method spends most of the total design time on nonlinear analysis. Thus, the NROESL algorithm makes the equivalent static load cases for each response and repeatedly performs linear response optimization and uses them as multiple loading conditions. The equivalent static loads are defined as the loads in the linear analysis, which generates the same response field as those in non-linear analysis. The algorithm is validated for the convergence and the optimality. The function satisfies the descent condition at each cycle and the NROESL algorithm converges. It is mathematically validated that the solution of the algorithm satisfies the Karush-Kuhn-Tucker necessary condition of the original nonlinear response optimization problem. The NROESL algorithm is applied to two structural problems. Conventional optimization with sensitivity analysis using the finite difference method is also applied to the same examples. The results of the optimizations are compared. The proposed method is very efficient and derives good solutions.

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계층 구조 클러스터링 알고리즘 설계 및 그 응용 (Design of Hierarchically Structured Clustering Algorithm and its Application)

  • 방영근;박하용;이철희
    • 산업기술연구
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    • 제29권B호
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    • pp.17-23
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    • 2009
  • In many cases, clustering algorithms have been used for extracting and discovering useful information from non-linear data. They have made a great effect on performances of the systems dealing with non-linear data. Thus, this paper presents a new approach called hierarchically structured clustering algorithm, and it is applied to the prediction system for non-linear time series data. The proposed hierarchically structured clustering algorithm (called HCKA: Hierarchical Cross-correlation and K-means clustering Algorithms) in which the cross-correlation and k-means clustering algorithm are combined can accept the correlationship of non-linear time series as well as statistical characteristics. First, the optimal differences of data are generated, which can suitably reveal the characteristics of non-linear time series. Second, the generated differences are classified into the upper clusters for their predictors by the cross-correlation clustering algorithm, and then each classified differences are classified again into the lower fuzzy sets by the k-means clustering algorithm. As a result, the proposed method can give an efficient classification and improve the performance. Finally, we demonstrates the effectiveness of the proposed HCKA via typical time series examples.

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Improved Gradient Direction Assisted Linking Algorithm for Linear Feature Extraction in High Resolution Satellite Images, an Iterative Dynamic Programming Approach

  • Yang, Kai;Liew, Soo Chin;Lee, Ken Yoong;Kwoh, Leong Keong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.408-410
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    • 2003
  • In this paper, an improved gradient direction assisted linking algorithm is proposed. This algorithm begins with initial seeds satisfying some local criteria. Then it will search along the direction provided by the initial point. A window will be generated in the gradient direction of the current point. Instead of the conventional method which only considers the value of the local salient structure, an improved mathematical model is proposed to describe the desired linear features. This model not only considers the value of the salient structure but also the direction of it. Furthermore, the linking problem under this model can be efficiently solved by dynamic programming method. This algorithm is tested for linear features detection in IKONOS images. The result demonstrates this algorithm is quite promising.

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A Study on Linear Matrix Inequalities Robust Active Suspension Control System Design Algorithm

  • Park, Jung-Hyen
    • Journal of information and communication convergence engineering
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    • 제6권1호
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    • pp.105-109
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    • 2008
  • A robust optimal control system design algorithm in active suspension equipment adopting linear matrix inequalities control system design theory is presented. The validity of the linear matrix inequalities robust control system design in active suspension system through the numerical examples is also investigated.

선형해석버버에 의한 점대응 움직임 추정 연구 : Degenerate Case에 대한 대책에 관하여 (Linear Algorithm for Motion Estimation from Point Correspondences over Two Perspective Views: How to Handle Degenerate Cases)

  • Shim, Young-Serk
    • 대한전자공학회논문지
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    • 제26권11호
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    • pp.1850-1856
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    • 1989
  • For determining motion/structure of a 3-D rigid object from point correspondences over two perspective views, a linear algorithm was developed in Refs. 3 and 4. This algorithm fails when the 3-D points under observation satisfy certain geometrical constraints, as demonstrated in Refs. 7 and 8. In the present paper, we show that the linear algorithm can be resurrected in these degenerate cases by adding additional lower order polynomial constraints to original equations.

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차분진화 알고리즘을 이용한 지역 Linear Discriminant Analysis Classifier 기반 패턴 분류 규칙 설계 (Design of Pattern Classification Rule based on Local Linear Discriminant Analysis Classifier by using Differential Evolutionary Algorithm)

  • 노석범;황은진;안태천
    • 한국지능시스템학회논문지
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    • 제22권1호
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    • pp.81-86
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    • 2012
  • 본 논문에서는 전형적인 Linear Discriminant Analysis을 확장시켜 전체 입력공간을 다수의 지역공간으로 분할하고 분할된 공간에 Local Linear Discriminant Analysis 기반으로 하여 패턴 분류 규칙을 설계하는 새로운 방법을 제안한다. 전체 입력공간을 여러 개의 지역공간으로 분할하기 위한 방법으로 unsupervised clustering의 대표적인 방법인 k-Means 클러스터링 기법과 최적화 알고리즘인 차분 진화 연산 알고리즘을 사용한다. 제안된 알고리즘의 성능 평가를 위해 기존의 패턴 분류기와 비교 결과를 제시한다.