水轮机调速模型

svpwm的MATLAB仿真实现 ，此程序用于svpwm的S-function的建立(MATLAB simulation implementation of SVPWM)

利用VORONOI算法在PYTHON中的多晶材料建模(Modeling of Polycrystalline Materials in PYTHON Using VORONOI Algorithms)

节点度是指和该节点相关联的边的条数，又称关联度。 特别地，对于有向图， 节点的入度 是指进入该节点的边的条数; 节点的出度是指从该节点出发的边的条数。(Node degree refers to the number of edges associated with the node, also known as the degree of association. In particular, for a directed graph, The ingress of a node is the number of edges entering the node; The out-degree of a node is the number of edges that start from that node.)

fluent教程（中文帮助+UDF完全使用手册）个人由英文文档翻译，仅供参考(Fluent tutorial (Chinese help +UDF complete manual) personal English translation of the document, for reference only.)

这个是信号与处理专业的大作业，主要研究两个方面的问题：低通滤波器的阶跃响应特性分析和连续线性系统的求解。通过这次课程设计，将会研究Matlab的一些基本的数值计算应用方法，对计算结果进行形象化地展示，有利于加深对本课程内容的理解。(This is a major task of signal and processing specialty. It mainly studies two aspects: step response characteristic analysis of low-pass filter and solution of continuous linear system. Through this course design, we will study some basic numerical calculation application methods of MATLAB, and visualize the calculation results, which is conducive to deepening the understanding of the course content.)

实现了random waypoint模型(random waypoint model)

说明：  用MACCORMACK方法求解一维LAVAL管亚音速流动(solve one dimensional laval tube with the method in maccormack)

说明：  本程序是完成网络的评价路径长度和聚类系数的计算。(This program is to calculate the average path length and clustering coeffient of a network.)

自适应（ self-adaptive）是指处理和分析过程中,根据处理数据的数据特征自动调整处理方法、处理顺序、处理参数、边界条件或约束条件,使其与所处理数据的统计分布特征、结构特征相适应,以取得最佳的处理效果(Self-adaptive refers to the automatic adjustment of processing methods, processing sequence, processing parameters, boundary conditions or constraints according to the data characteristics in the process of processing and analysis, so as to adapt them to the statistical distribution characteristics and structural features of the processed data, so as to achieve the best processing effect.)

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.)