IEEE39_BPA_PSSE

说明：  二阶离散多智能体系统的二层邻居一致性算法研究成果(Discrete_system_for_second_order_neighbor_consensus_algorithm)

蓄电池双向Boost/Buck充放电控制，与电网结合。(Battery bi-directional Boost/Buck charge and discharge control, combined with the grid.)

通过设置不同的参数，创建小世界网络，用于仿真建模。(This program is to create a small world network for simulation.)

说明：  转子系统启动时的瞬态动力学分析，有限元分析(Transient Dynamics Analysis of Rotor System at Start-up)

三相永磁同步电机的滞环电流控制仿真模型，控制瞬态电流输出。(Simulation Model of hysteresis current Control for Three-phase permanent Magnet synchronous Motor)

动态因子copula模型建模并模拟分析系统性风险(Dynamic Factor Copula Model Modeling and Simulating Analysis of Systematic Risks)

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.)

求解二维拉普拉斯方程的matlab程序的实现(Solving two-dimensional Laplace equation)

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：  ARIMA整合移动平均自回归模型，时间序列预测分析方法之一，可用于股价预测。(ARIMA integrates moving average autoregressive model and time series forecasting analysis method, which can be used for stock price forecasting.)