Newton迭代法解非线性方程组

算法分析与设计 0-1背包问题四种不同算法的实现 C语言实现 贪心算法总是作出在当前看来是最好的选择，即贪心算法并不从整体最优解上加以考虑，它所作出的选择只是在某种意义上的局部最优解。贪心算法不是对所有问题都能得到整体最优解，但对范围相当广的许多问题它能产生整体最优解。在一些情况下，即使贪心算法不能得到整体最优解，但其最终结果却是最优解的很好近似解。

数值计算之牛顿插值，包含matlab代码实现！-Numerical calculation of the Newton interpolation, including the matlab code to achieve!

Option Explicit Option Base 1     Dim sAngle() As Double, sdAngle() As Double, sEdge() As Double, s0Edge() As Double     "分别存放角度观测值、坐标方位角、观测边长和近似边长     Dim ajk() As Double, bjk() As Double    "坐标方位角改正数的系数     Dim detX() As Double, detY() As Double, reX() As Double, reY() As Double     "分别存放各测站相对于导线中前一结点的X、Y坐标增量和坐标闭合差     Dim strFileName As String               "存放数据文件名（含路径）     Dim iType%, iAngleType%, Xa#,

这是一个超长整数加法.转载.-This is a long integers. Reprinted.

在数据库中发现频繁模式和关联规则是数据挖掘领域的最基本、最重要的问题。大多数早期的研究采用了类似Apriori算法的产生候选级并测试迭代的途径代价是昂贵的，尤其是挖掘富模式和长模式时，Jiawei Han提出了一种新颖的数据结构FP_tree,及基于其上的FP_growth算法，主要用于有效的进行长模式与富模式的挖掘.本文在讨论了FP_growth算法的基础上，提出了用Visual C++实现该算法的方法，并编写了算法的程序。-found in the database model and the frequent association rules is the area of data mining the most fundamental and important issues. Most of the early studies used a similar Apriori algorithm for the selection of candidates and test-iterative way was costly, particularly mining the rich patterns and long model, Jiawei Han proposed a novel data structure FP_tree and on the basis of their FP_growth algorithm used effectively the model for long and rich patterns of excavation. This paper discussed the FP_growth algorithm on the basis of the Visual C of the algorithm, and the preparation procedure of the algorithm.

解稀疏对称方程组的ICCG法fortran源程序 有算例，希望对你有帮助-Solution of sparse symmetric linear ICCG method source fortran examples there, and they hope to help you

计算两个日期间的天数差-calculate the day interval between two datetime value

VB中不使用 on error goto的容错程序。-not use VB on the fault-tolerant error goto procedures.

用VB实现优化计算的智能算法-VB Intelligent Optimization Algorithm

意大利保罗.基迪茨著，国内著名高校学些翻译。经典的有关数据挖掘的教材。 -Italian Paul.基迪茨, and domestic well-known colleges and universities learn more Translation. Classical data mining-related teaching materials.