K-means 的C++实现

工程计算中经常用到的数值vc算法，对于进行数值模拟的网友很有用-engineering calculation frequently used vc numerical algorithm for the numerical simulation of netizens useful

LRU最近最少使用算法-LRU algorithm used recently, at least

用c语言编辑数据库中的最小函数依赖， 求属性集X（XU）关于U上的函数依赖集F 的闭包XF+

一个很小的程序,可以进行字符串比较,适合初学者学习,很容易读懂的-a small procedure can be carried out strings, for beginners to learn, it is easy to understand the

这是二分法求根的源码-This is the dichotomy of the source Root

%初始化参数 %注：popsize=200,MaxGeneration=100,约跑2分钟。若不要求太精确，可减少循环次数。pointnumber=11;                            %节点个数Popsize=200;                               %种群规模，只能取偶数（因67行的循环）MaxGeneration=100;                         %最大代数Pc=0.8;Pm=0.3;                             %交叉概率和变异概率A=[0 2 8 1 50 50 50 50 50 50 50    2 0 6 50 1 50 50 50 50 50 50    8 6 0 7 50 1 50 50 50 50 50    1 50 7 0 50 50 9 50 50 50 50    50 1 50 50 0 3 50 2 50 50 50    50 50 1 50 3 0 4 50 6 50 50    50 50 50 9 50 4 0 50 50 1 50    50 50 50 50 2 50 50 0 7 50 9    50 50 50 50 50 6 50 7 0 1

this the firmware provided freely for the trf7960

本代码为基本粒子群算法，通过修改适应值函数，可以应用于多个领域，比如电力系统的相关参数的优化设置，如陷入局部最优，需引入变异函数，通过重置某一维的数值，使粒子脱离局部最优。

Fortran 90

平均因子分解法，适用于正定矩阵First, let s recall the definition of the Cholesky decomposition: Given a symmetric positive definite square matrix X, the Cholesky decomposition of X is the factorization X=U U, where U is the square root matrix of X, and satisfies: (1) U U = X (2) U is upper triangular (that is, it has all zeros below the diagonal). It seems that the assumption of positive definiteness is necessary. Actually, it is "positive definite" which guarantees the existence of such kind of decomposition. -Average factor decomposition method applied to positive definite matrix First, let s recall the definition of the Cholesky decomposition: Given a symmetric positive definite square matrix X, the Cholesky decomposition of X is the factorization X = UU, where U is the square root matrix of X, and satisfies: (1) UU = X (2) U is upper triangular (that is, it has all zeros below the diagonal). It seems that the assumption of positive definiteness is necessary. Actually, it is positive