微电网优化

极小 算法（Min-Min）、极大极小算法(Max-Min)、最大时间跨度算法（Max-Int）三种典型的映射算法的算法原理以及计算程序(Minimal algorithm (Min-Min), max-min algorithm (Max-Min), maximum time-span algorithm (Max-Int) three typical mapping algorithm and the algorithm of the calculation program)

fluent中用于修改湍流粘度系数的自定义函数(udf to modify turbulence viscosity coefficient in fluent)

世界上最好的微积分教材，搞程序的，研究的，数学的都应该了解，这个是James.Stewart的Calculus第七版，英文原版，彩色的，值得珍藏。(The world' s best calculus textbook, engage in programs, research, mathematics should understand that this is James.Stewart seventh edition of Calculus, English original, colorful and worth treasuring.)

计算方法实验，通过编程实现埃特金加速法，一般迭代法，牛顿法的收敛次数的计算(calculated experiment, Programming Aitken acceleration method, the general iterative method, the convergence of Newton's method of calculating the number of)

多种曲线拟合方法，包括埃尔米特插值，差商，牛顿法，龙格库塔法( U591A u79CD u66F2 u7EBF u62DF u5408 u65B9 u6CD5 uFF0C u5305 u62EC u57C3 u5C14 u7C93 u7279 u63D2 u503C uFF0C u5DEE u5546 uFF0C u725B u987F u6CD5 uFF0C U9F99 u683C u5E93 u5854 u6CD5)

2维TE波的FDTD的源程序。周期边界条件，有限宽度的吸收边界条件(Two-dimensional TE wave FDTD source. Periodic boundary conditions, the limited width of the absorbing boundary conditions)

This source file contains example PitchCntrl(), UserHSSBr(), ! UserVSCont(), and UserYawCont() routines that are used to interface ! FAST with a master controller implemented as a dynamic-link-library ! (DLL) in the style of Garrad Hassan s Bladed wind turbine software ! package. All four routines call routine BladedDLLInterface(), which ! contains a call to the Bladed-style DLL that evaluates as DISCON(). ! Routine BladedDLLInterface() USEs a MODULE named ! BladedDLLParameters(), which stores values of PARAMETER constants ! used in the interface.

实现有限域中乘法，输入二个普通二级制数，输出在本原多项式的乘法结果(Achieve limited multiplication field, enter the number of two-tier system of two ordinary output in primitive polynomial multiplication results)

An example of using a matrix object in order to pass values and complete a function.

hartigans Sequential Leader Clustering Algorithm in terms of OpenCV (ver.1.1) Sequential Leader algorithm: Hartigan, J. A. (1975), Clustering Algorithms. John Wiley and Sons, Inc., New York, NY. 1. Select maximum cluster "radius" 2. Start with zero clusters 3. Add each item to be clustered to: * Closest cluster if distance <= r * New cluster if distance to closest cluster > r 4. Compute new center from members in cluster 5. Empty the clusters (keeping the centers) 6. Return to step 3 (until no changes are made)