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10.1.1.25.3645

于 2011-01-17 发布 文件大小:192KB
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下载积分: 1 下载次数: 5

代码说明:

  Photonic crystal is discribed in this matlab code please notice that it does not compatible with any work you want to do,you may modify it to use.

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    Improved differential evolution algorithm to optimize the hybrid particle swarm optimization intelligent optimization algorithm source code
    2013-12-10 05:27:53下载
    积分:1
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    This code for target tracker in matlab
    2013-11-16 23:46:01下载
    积分:1
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    粒子群算法的改进,粒子在搜索过程中,适应值大的部分粒子,运动方向反方向运动,扩大了搜索范围,避免早熟。通过函数测试可用。(Particle swarm algorithm, part of the particle motion direction opposite direction, expanding the scope of the search to avoid premature. Through function test available.)
    2011-07-09 10:30:28下载
    积分:1
  • Metal-dielectric
    该程序用于解决光学领域金属介质膜参数的问题,运行速度快。(The procedures for the settlement of the optical field of metal dielectric film parameter problem, fast running speed.)
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  • 针对风电场短期风速的预测提出一种基于小波变换的组合预测方法 Wind-Speed-Combined-Prediction
    针对风电场短期风速的预测提出一种基于小波变换的组合预测方法。首先利用Mallat 算法对短期风速时间序列进行db3 小波三层分解与重构,得到短期风速时间序列的近似分量和细节分量。针对近似分量和细节分量的不同特性,对近似分量利用粒子群算法优化的最小二乘支持向量机进行预测,对细节分量利用自回归求和滑动平均模型进行预测。最后各预测模型预测值组合叠加得到最终的短期风速预测值。仿真结果表明该方法具有较高的预测准确度。(In order to improve short-term wind speed prediction accuracy of wind farms,a combined prediction method based on the wavelet transform is proposed. Firstly,the db3 wavelet is used for three-layer decomposition and reconstruction for short-term wind speed time series through Mallat algorithm. The approximation components and the detail components of the short-term wind speed are then obtained. Next,according to the different characteristics of these components,the least square support vector machine optimized by particle swarm algorithm and the autoregressive integrated moving average model are adopted as the predictivemodels for the approximate components and the detail components respectively. Then,the final predictive value of the short-term wind speed is obtained by the combination of the two components. The simulation results indicate that higher accuracy can be obtained in this prediction method.)
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