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MATLAB-Code

于 2021-04-22 发布文件大小:14KB

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下载积分: 1 下载次数: 50

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代码说明：

有限元几何非线性算例程序(FEM MATLAB Code for Geometrical Nonlinear Analysis)

文件列表：

MATLAB Code
...........\Assemble.m,1003,2015-11-30
...........\BoundaryCondition.asv,2310,2015-11-30
...........\BoundaryCondition.m,2300,2015-11-30
...........\constraints.m,813,2015-11-30
...........\elementdof.m,746,2011-07-02
...........\Force.m,665,2015-11-30
...........\GaussQuadrature.m,1880,2015-05-11
...........\InitialStressMatrix.m,2296,2015-11-30
...........\Jacobian.m,1172,2015-09-21
...........\MeshRectangular.m,2572,2015-11-30
...........\NonLinearMain.m,4613,2015-11-30
...........\PlateBendingLinear.m,722,2015-11-30
...........\PlateInplaneNonlinear.m,1420,2015-09-30
...........\PlotFieldonDefoMesh.m,1940,2015-11-30
...........\PlotFieldonMesh.m,1863,2015-11-30
...........\PlotMesh.m,1645,2015-05-28
...........\SDF.m,4530,2015-11-30
...........\SetColorbar.m,890,2011-09-26
...........\ShapeDerivativeForInitialStressMatrix.m,334,2015-09-30
...........\ShapefunctionDerivatives.m,1073,2015-05-28
...........\Shapefunctions.m,1317,2015-05-28

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说明：这是一个基于蚁群智能算法的组播QOS路由问题程序代码。(This is a multicast QoS problem based on AC.)

2011-03-06 22:03:57下载

积分：1
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2009-04-25 10:51:04下载

积分：1
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一种harris的改进方法，值得借鉴，一篇很好的参考论文！(Harris an improved method, is worth learning, a good reference paper!)

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It contains the methods to extract out the darker or lighter objects of various intensities and shapes (including faint/ low intensity objects) noisy or inhomogeneous background

2015-01-23 17:45:06下载

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用于潮汐模拟计算；能计算相关模型；包括两部分：1是用户界面编程2是预测潮汐等(TMD (Tide Model Driver)TMD is a Matlab package for accessing the harmonic constituents for the ESR/OSU family of high-latitude tide models, and for making predictions of tide height and currents. TMD includes two components: (1) a graphical user interface (GUI) for quickly browsing tide fields, zooming in on regions of interest, and selecting points and time ranges for predictions of specific variables and (2) a set of scripts for accessing tide fields and making predictions. Each component is described below.)

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