geng

此代码属于地球物理领域，是用有限差分开发的直流电法三维正演，基于FORTRAN平台，此代码具有很高的运算效率，对于从事地球物理领域的人来说是不可多得的(This code belongs to the field of geophysics, is developed using finite difference method of three-dimensional forward modeling of DC, FORTRAN-based platform, this code has high computing efficiency, people engaged in geophysical field is rare)

计算低速气动力的涡格法程序，来自NASA，可信度高(This is a vortex lattice aerodynamic program from the low speed aerodynamics group at NASA Langley)

基于matlab的约束非线性规划算法库，适于学习！(Matlab-based algorithm for the constrained nonlinear programming library, suitable for learning!)

abaqus子程序fric摩擦材料clough-duncan模型，二三维通用，已经验证(abaqus subroutine frictional material fric)

求解激波管问题等产生的偏微分方程组的各种数值算法。(Shock tube problem solving, such as partial differential equations arising from a variety of numerical algorithm.)

支持向量机和BP神经网络都可以用来做非线性回归拟合，但它们的原理是不相同的，支持向量机基于结构风险最小化理论，普遍认为其泛化能力要比神经网络的强。大量仿真证实，支持向量机的泛化能力强于BP网络，而且能避免神经网络的固有缺陷——训练结果不稳定。本源码可以用于线性回归、非线性回归、非线性函数拟合、数据建模、预测、分类等多种应用场合(Support vector machines and BP neural network can be used for non-linear regression fit, but they is not the same principle, support vector machine based on structural risk minimization theory, generally considered its generalization ability than the neural network of strong . Inherent defect- a large number of simulation confirmed that generalization ability of support vector machine is stronger than the BP network, but also to avoid neural network training results unstable. The source code can be used for linear regression, nonlinear regression, nonlinear function fitting a variety of applications, data modeling, forecasting, classification)

说明：  编程观察无穷级数 1/n的收敛性。 采用 IEEE 单精度浮点数，观察当 n 为何值时求和结果不再变化，将它与理论分析的结论进 行比较 (注：在 MATLAB 中可用 single 命令将变量转成单精度浮点数)。(Programming observation of convergence of infinite series 1/n)

说明：  使用Eviews编写covar程序，实现covar的计算(Using Eviews to write Covar)

通过滑动T检验时间序列的变化趋势，一般多用于气象分析(T-test time series by sliding the trend, generally used for weather analysis)

说明：  非常详细的umat 雅可比矩阵更新算法的讲解(detailed describetion of the jacobian matrix in abaqus umat)