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CS model and kalman

于 2018-09-08 发布文件大小:119KB

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代码说明：

单机动目标跟踪作业，有具体的程序使用说明(There are specific procedures to explain the operation of single machine moving target tracking.)

文件列表：

homework\Karlman.asv, 613 , 2006-05-26
homework\Karlman.m, 876 , 2006-06-05
homework\main.asv, 1556 , 2006-06-03
homework\main.m, 1880 , 2006-06-13
homework\Trace.asv, 996 , 2006-05-26
homework\Trace.m, 1086 , 2006-06-13
homework\机动目标跟踪_张泽兵_05040056.doc, 200704 , 2006-06-05
homework, 0 , 2006-06-05
homework\untitled1.fig, 7847 , 2009-05-25
homework\untitled2.fig, 7962 , 2009-05-25
homework\untitled3.fig, 15580 , 2009-05-25

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2017-10-29 16:46:09下载

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2018-05-27 16:15:59下载

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2019-04-11 16:34:20下载

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说明：丹麦大学研究建立的风力发电机模型，2MW风机，包括叶轮、齿轮箱、发电机等风机系统仿真模型。(The wind turbine model established by the University of Denmark, 2MW wind turbine, including impeller, gearbox, generator and other complete simulation models.)

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大坝变形的精确预测对其安全评价方面发挥着重要作用。为了进一步提高大坝变形预测精度，提出了一种改进的灰狼算法优化支持向量机的预测模型。通过引入非线性收敛因子和采用动态加权策略，提升灰狼算法优化支持向量机惩罚因子和核函数参数的能力，并以优化的参数来建立支持向量机大坝变形预测模型。选取实例数据，在与布谷鸟算法、差分进化算法、粒子群算法、基本灰狼算法优化的支持向量机预测比较中，实验结果表明，改进的灰狼算法对支持向量机参数的优化是有效的，可以提高大坝变形预测精度。(Accurate prediction of dam deformation plays an important role in its safety evaluation. In order to further improve the prediction accuracy of dam deformation, an improved grey Wolf algorithm is proposed to optimize the prediction model of support vector machine. By introducing the nonlinear convergence factor and using the dynamic weighting strategy, the gray wolf algorithm is improved to optimize the capacity of the support vector machine penalty factor and the kernel parameter, and the support vector machine dam deformation prediction model is established with the optimized parameters. The experimental results show that the Improved Grey Wolf algorithm is effective for the optimization of support vector machine parameters, and it can improve the accuracy of the deformation prediction of the dam.)

2018-06-28 09:53:07下载

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2021-04-26 11:18:45下载

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2021-03-22 21:19:16下载

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CS model and kalman

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