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ANSYS-earthquake-wave-input-node-
利用文中命令码，可以在ANSYS中实现如何输入地震波，这对结构动力分析非常重要！(Using text command code, can be implemented in ANSYS how to input seismic wave, which is very important for structural dynamic analysis!)
- 2014-09-20 10:00:56下载
- 积分：1
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Gaussian_bif
Gaussian映射的分岔图，非线性动力学，MATLAB(Gaussian map bifurcation, Nonlinear dynamics, MATLAB)
- 2011-10-08 18:38:41下载
- 积分：1
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CI
说明： 估计融合算法里面，经典算法CI算法的实现，针对了CV和CA模型(Inside estimation fusion algorithm, the classical algorithm CI algorithm, for the CV and CA model)
- 2016-06-13 09:44:46下载
- 积分：1
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wavemoni
说明： 利用MATLAB模拟二维海浪，直接运行即可。简单好用。(Using MATLAB to simulate two dimensional sea waves, it can run directly. It's easy to use.)
- 2018-02-10 08:08:48下载
- 积分：1
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LowPassFirFliter
the low pass filter, including the test data
- 2011-07-20 22:05:47下载
- 积分：1
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power_VariableInductor
power_VariableInductor.rar,功率电子领域matlab仿真文件，已经验证过，程序运行正常(power_VariableInductor.rar,Power electronics field matlab simulation file, has already been verified, the normal operating procedures)
- 2013-08-26 22:20:58下载
- 积分：1
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owners
Script generates list of owners for files in choose directory
- 2014-10-27 22:17:41下载
- 积分：1
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基于微观交通流建模中运用车辆跟驰模型方法
基于微观交通流建模中运用车辆跟驰模型方法 进行仿真 车辆更新(Use of car-following model method based on microscopic traffic flow modeling simulation vehicle updates)
- 2013-03-30 16:44:37下载
- 积分：1
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referentiel
MATLAB instruction mimo
- 2011-11-16 03:52:32下载
- 积分：1
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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.)
- 2016-12-23 10:12:27下载
- 积分：1
