Low Turbulence Model

共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(Conjugate gradient method (Conjugate Gradient) is between the steepest descent method between the method and Newton' s method, it takes only a first derivative information, but to overcome the steepest descent method convergence slow shortcomings, but also to avoid the Newton method needs to be stored Hesse and disadvantages of computing inverse matrix and the conjugate gradient method is not only one of the most useful methods to solve large linear equations, solution of large-scale nonlinear optimization is one of the most effective algorithm. In various optimization algorithm, conjugate gradient method is a very important one. The advantage is that a small amount of memory required, with step convergence, high stability, and does not require any external parameters.)

本程序是根据jacobi过关法求实对称矩阵的全部特征值和特征向量(This procedure is based on realistic method jacobi clearance of all symmetric matrix eigenvalue and eigenvectors)

由美国圣母大学Jena教授及其学生编写的关于计算半导体迁移率的matla脚本文件。(Jena professor from the University of Notre Dame and his students prepare for the calculation of a series of semiconductor mobility matlab script file.)

关于复数矩阵求导的一本经典书籍“Complex-valued_matrix_derivatives”的电子版(About the electronic version of the complex matrix derivation of a classic book " Complex-valued_matrix_derivatives" )

说明：  ABAQUS 的二次开发,详细注释说明，自学ABAQUS的二次开发(ABAQUS secondary development, detailed notes, self-study ABAQUS secondary development)

Computer Arithmetic (press 2000)

说明：  Fractal分形，简短的代码，清晰可用(Fractal)

MDVRP_遗传算法 可以运行 希望对大家有帮助(a solution to MDVRP ,i hope it can help you)

Faran散射模型，能够计算液体中球形物体的散射声压(The Faran scattering model, able to calculate the scattering of spherical objects in the liquid sound pressure)

潮流计算中拉丁超立方采样的算法，可利用其进行概率潮流计算(Flow calculation Latin hypercube sampling algorithm, can use its probabilistic load flow calculation)