UMAT-JC

根据试试数据 对变压器技术参数进行校核 利用的是最小二乘曲线拟合的方法(According to the data to try check technical parameters of the transformer is the least squares curve fitting using the method)

数值分析中解线性方程组，最常用的四种迭代方法：雅克比、高斯赛德尔、SOR、共轭梯度，以及他们的比较(numerical analysis : jacobi S-G、SOR、cong)

用matlab编写的cholesky分解程序，希望对大家有些帮助(Matlab prepared using Cholesky decomposition procedures, in the hope that some U.S. help)

计算流体动力学中湍流模型的源程序，代码十分宝贵(Computational fluid dynamics model of the source of turbulence, the code is very valuable)

说明：  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 Gradient) is a method between the steepest descent method and Newton's method. It only uses the first derivative information, but overcomes the disadvantage of slow convergence of steepest descent method, and avoids the disadvantage of storing and calculating Hesse matrix and solving inverse of Newton's method. Conjugate gradient method is not only one of the most useful methods to solve large-scale linear equations, but also the most effective method to solve large-scale nonlinear optimization One of the algorithms of. Among all kinds of optimization algorithms, conjugate gradient method is very important. It has the advantages of small storage, step convergence, high stability and no external parameters.)

说明：  MATLAB的一个使用工具箱，LINGO11汉化无限变量版。(A toolbox of MATLAB, LINGO11 Chinese Infinite Variable Edition.)

针对于对一般矩阵的求逆，或对复杂系统的求逆(Aimed at the general matrix inverse or inverse complex systems)

本代码为《最优化理论与方法》书籍重的信赖域算法的代码，本代码中的目标函数和约束等初值可由需要进行改变，来得到所期望的计算(The code for the " optimization theory and method" heavy books trust region algorithm code, the code of the objective function and constraints may need to change the initial value to get the desired calculation)

Code source of Finite Element Analysis with Error Estimators

求解任意区域上的二元函数的二重积分，功能强大实用方便！(Solving binary function on any area of ​ ​ the double integral, powerful practical and convenient!)