03CH4_red19

单纯形法，求解线性规划问题的通用方法。单纯形是美国数学家G.B.丹齐克于1947年首先提出来的。它的理论根据是：线性规划问题的可行域是 n维向量空间Rn中的多面凸集，其最优值如果存在必在该凸集的某顶点处达到。顶点所对应的可行解称为基本可行解。单纯形法的基本思想是：先找出一个基本可行解，对它进行鉴别，看是否是最优解；若不是，则按照一定法则转换到另一改进的基本可行解,再鉴别；若仍不是，则再转换,按此重复进行。因基本可行解的个数有限，故经有限次转换必能得出问题的最优解。如果问题无最优解也可用此法判别。 (Simplex method for the minimum)

利用ANSYS有限元仿真软件对复合材料进行异常检测仿真实验，程序为一损伤样板模型(ANSYS finite element simulation software for composites simulation anomaly detection, the program is a damage model model)

电力系统暂态分析中非常有用的三相短路计算程序，只要改变输入就可用于求解具体问题(power system transient analysis is very useful three-phase short-circuit the process. as long as the change in input can be used to solve specific problems)

很好很实用的信号处理程序。适合学习和科研参考使用。(Very good very useful signal processing. Suitable for learning and scientific research use and reference.)

unit commitment with Gams

插值法： （1）拉格朗日插值 （2）牛顿插值 （3）分段线性插值 （4）Hermite 插值 （5）样条插值(Interpolation method: (1) Lagrange Interpolation (2) Newton interpolation (3) piecewise linear interpolation (4) Hermite interpolation (5) spline interpolation)

说明：  一般的最小二乘通常是一次拿到全部的数据， 对所有数据进行统一优化计算得到模型系数。递推最小二乘是以一种递推的方式计算最小二乘，每次使用最新的测量值，来不断更新模型系数。(General least squares usually get all the data at one time, and perform unified optimization calculations on all the data to get the model coefficients. Recursive least squares is to calculate the least squares in a recursive way, each time the latest measured value is used to continuously update the model coefficients.)

用于利用最大熵法求解数据资料服从的分布类型。并应用最小二乘法求解模型以得到最优解(Using the maximum entropy method for solving the data distribution type of obedience. And apply the least squares method to obtain the optimal solution to solve the model)

求解声学问题的边界元程序，给声学研究的人员很大启发(Solving the problem of acoustic boundary element program, to inspire great acoustic research staff)

实现最小二乘的仿真函数，有3次和9次多项式的拟合。(Realize the simulation of least squares function, has 3 times and 9 times polynomial fitting.)