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说明：  将一个50Hz的干扰信号加入到白噪声中，然后对合成信号做fft，得到相应的幅频谱图和相位谱图。(A 50 Hz interference signal is added to the white noise, and then the composite signal is FFT to get the corresponding amplitude spectrum and phase spectrum.)

基于bpa的IEEE39节点算例，包含暂态数据和稳态数据(Example of IEEE39 node based on BPA)

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.)

说明：  该插件用于快速生成2维VORONOI图 请将文件解压到C盘-用户-abaqus_plugins文件夹下(This plug-in is used to generate 2D Voronoi graph quickly Please unzip the file to the C disk user ABAQUS plugins folder)

说明：  用牛顿-拉夫逊法进行电力系统潮流分布计算(Calculation of Power Flow Distribution in Power System by Newton-Raphson Method)

说明：  主要可以用来研究疲劳累积循环载荷作用下损伤与断裂问题，(It can be used to study the damage and fracture under the fatigue cumulative cyclic load,)

新的屈服准则ABAQUS子程序UMAT，含有多种较新的准侧，能很好运用(The new yield criterion ABAQUS subroutine UMAT contains a variety of newer standards and can be used very well.)

说明：  采用simulink搭建IEEE标准33节点仿真模型及.m程序(IEEE standard 33 node simulation model)

说明：  umat基础知识教学，适合刚接触UMAT的新手做参考(UMAT basic knowledge teaching, suitable for beginners)

说明：  极大使然系统辨识 例程 拓展性强 适合动态系统的辨识和使用(Identification of the most important system routine Expansibility)