2d-MT-finite-element-forward-

说明：  数学建模 马尔科夫链的详细讲解 马尔科夫链的详细讲解 数学建模(A detailed explanation of markov chains for mathematical modeling)

说明：  基于python的多项式曲线拟合，本程序以1 3 5 9次为例子。(Based on the polynomial curve fitting of python, this program takes 1 3 5 9 times as an example.)

几何绕射理论，是高频解决电磁场问题的方法，本书很具有代表性(GTD is a high-frequency electromagnetic fields to solve the problem, this book is a representative)

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(Conjugate gradient method (Conjugate Gradient) is between the steepest descent method and Newton' s method between a method that takes only a first derivative information, but to overcome the slow convergence of the steepest descent method shortcomings, but also avoid the need to store Newton and computing the inverse Hesse matrix and disadvantages, conjugate gradient method is not only to solve large linear equations of the most useful methods, large-scale nonlinear optimization solution is the most efficient algorithms)

约束最优化方法－－最速下降法(也叫梯度法)，是人们用来求多个变量函数极值问题的最早的一种方法。(Constrained optimization methods- steepest descent method (also known as gradient method), is used for multiple variables function Extremum Problems earliest methods.)

nelder-mead algorithm for unconstrained optimization simulation in c programming language

说明：  Dsimplex.m 对偶单纯形法求解线性规划问题(Dual simplex method for solving linear programming problems)

说明：  本模拟是采用分步傅里叶的解，求光孤子在光线内传输过程数值求解薛定谔方程。方程是激光器在光纤中传输的过程。(In this simulation, the fractional Fourier solution is used to solve the Schrodinger equation. The equation is the process of laser transmission in fiber.)

外点罚函数方法，可以用来求解约束优化问题，也可以用来被调用在智能算法中(Point outside the penalty function can be used for solving constrained optimization problems, can also be used in intelligent algorithm called)

说明：  APdL参数化有限元分析技术及其应用实例(APdL parameterized finite element analysis techniques and its application)